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Sample records for constrained optimization formulation

  1. Robust and Reliable Portfolio Optimization Formulation of a Chance Constrained Problem

    Sengupta Raghu Nandan

    2017-02-01

    Full Text Available We solve a linear chance constrained portfolio optimization problem using Robust Optimization (RO method wherein financial script/asset loss return distributions are considered as extreme valued. The objective function is a convex combination of portfolio’s CVaR and expected value of loss return, subject to a set of randomly perturbed chance constraints with specified probability values. The robust deterministic counterpart of the model takes the form of Second Order Cone Programming (SOCP problem. Results from extensive simulation runs show the efficacy of our proposed models, as it helps the investor to (i utilize extensive simulation studies to draw insights into the effect of randomness in portfolio decision making process, (ii incorporate different risk appetite scenarios to find the optimal solutions for the financial portfolio allocation problem and (iii compare the risk and return profiles of the investments made in both deterministic as well as in uncertain and highly volatile financial markets.

  2. A multi-fidelity analysis selection method using a constrained discrete optimization formulation

    Stults, Ian C.

    The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model

  3. Evolutionary constrained optimization

    Deb, Kalyanmoy

    2015-01-01

    This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful...

  4. The Regularized Fast Hartley Transform Optimal Formulation of Real-Data Fast Fourier Transform for Silicon-Based Implementation in Resource-Constrained Environments

    Jones, Keith

    2010-01-01

    The Regularized Fast Hartley Transform provides the reader with the tools necessary to both understand the proposed new formulation and to implement simple design variations that offer clear implementational advantages, both practical and theoretical, over more conventional complex-data solutions to the problem. The highly-parallel formulation described is shown to lead to scalable and device-independent solutions to the latency-constrained version of the problem which are able to optimize the use of the available silicon resources, and thus to maximize the achievable computational density, th

  5. Linearly constrained minimax optimization

    Madsen, Kaj; Schjær-Jacobsen, Hans

    1978-01-01

    We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...

  6. Constrained Optimal Transport

    Ekren, Ibrahim; Soner, H. Mete

    2018-03-01

    The classical duality theory of Kantorovich (C R (Doklady) Acad Sci URSS (NS) 37:199-201, 1942) and Kellerer (Z Wahrsch Verw Gebiete 67(4):399-432, 1984) for classical optimal transport is generalized to an abstract framework and a characterization of the dual elements is provided. This abstract generalization is set in a Banach lattice X with an order unit. The problem is given as the supremum over a convex subset of the positive unit sphere of the topological dual of X and the dual problem is defined on the bi-dual of X. These results are then applied to several extensions of the classical optimal transport.

  7. Slope constrained Topology Optimization

    Petersson, J.; Sigmund, Ole

    1998-01-01

    The problem of minimum compliance topology optimization of an elastic continuum is considered. A general continuous density-energy relation is assumed, including variable thickness sheet models and artificial power laws. To ensure existence of solutions, the design set is restricted by enforcing...

  8. Trends in PDE constrained optimization

    Benner, Peter; Engell, Sebastian; Griewank, Andreas; Harbrecht, Helmut; Hinze, Michael; Rannacher, Rolf; Ulbrich, Stefan

    2014-01-01

    Optimization problems subject to constraints governed by partial differential equations (PDEs) are among the most challenging problems in the context of industrial, economical and medical applications. Almost the entire range of problems in this field of research was studied and further explored as part of the Deutsche Forschungsgemeinschaft (DFG) priority program 1253 on “Optimization with Partial Differential Equations” from 2006 to 2013. The investigations were motivated by the fascinating potential applications and challenging mathematical problems that arise in the field of PDE constrained optimization. New analytic and algorithmic paradigms have been developed, implemented and validated in the context of real-world applications. In this special volume, contributions from more than fifteen German universities combine the results of this interdisciplinary program with a focus on applied mathematics.   The book is divided into five sections on “Constrained Optimization, Identification and Control”...

  9. Constrained optimization via simulation models for new product innovation

    Pujowidianto, Nugroho A.

    2017-11-01

    We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

  10. Order-constrained linear optimization.

    Tidwell, Joe W; Dougherty, Michael R; Chrabaszcz, Jeffrey S; Thomas, Rick P

    2017-11-01

    Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data. © 2017 The British Psychological Society.

  11. Excision technique in constrained formulations of Einstein equations: collapse scenario

    Cordero-Carrión, I; Vasset, N; Novak, J; Jaramillo, J L

    2015-01-01

    We present a new excision technique used in constrained formulations of Einstein equations to deal with black hole in numerical simulations. We show the applicability of this scheme in several scenarios. In particular, we present the dynamical evolution of the collapse of a neutron star to a black hole, using the CoCoNuT code and this excision technique. (paper)

  12. Conditions for the Solvability of the Linear Programming Formulation for Constrained Discounted Markov Decision Processes

    Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Institut de Mathématiques de Bordeaux, INRIA Bordeaux Sud Ouest, Team: CQFD, and IMB (France); Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es [UNED, Department of Statistics and Operations Research (Spain)

    2016-08-15

    We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.

  13. Security constrained optimal power flow by modern optimization tools

    Security constrained optimal power flow by modern optimization tools. ... International Journal of Engineering, Science and Technology ... If you would like more information about how to print, save, and work with PDFs, Highwire Press ...

  14. A technique for determining the optimum mix of logistics service providers of a make-to-order supply chain by formulating and solving a constrained nonlinear cost optimization problem

    Mrityunjoy Roy

    2013-04-01

    Full Text Available In this paper, a technique has been developed to determine the optimum mix of logistic service providers of a make-to-order (MTO supply chain. A serial MTO supply chain with different stages/ processes has been considered. For each stage different logistic service providers with different mean processing lead times, but same lead time variances are available. A realistic assumption that for each stage, the logistic service provider who charges more for his service consumes less processing lead time and vice-versa has been made in our study. Thus for each stage, for each service provider, a combination of cost and mean processing lead time is available. Using these combinations, for each stage, a polynomial curve, expressing cost of that stage as a function of mean processing lead time is fit. Cumulating all such expressions of cost for the different stages along with incorporation of suitable constraints arising out of timely delivery, results in the formulation of a constrained nonlinear cost optimization problem. On solving the problem using mathematica, optimum processing lead time for each stage is obtained. Using these optimum processing lead times and by employing a simple technique the optimum logistic service provider mix of the supply chain along with the corresponding total cost of processing is determined. Finally to examine the effect of changes in different parameters on the optimum total processing cost of the supply chain, sensitivity analysis has been carried out graphically.

  15. Neuroevolutionary Constrained Optimization for Content Creation

    Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian

    2011-01-01

    and thruster types and topologies) independently of game physics and steering strategies. According to the proposed framework, the designer picks a set of requirements for the spaceship that a constrained optimizer attempts to satisfy. The constraint satisfaction approach followed is based on neuroevolution...... and survival tasks and are also visually appealing....

  16. Stress-constrained topology optimization for compliant mechanism design

    de Leon, Daniel M.; Alexandersen, Joe; Jun, Jun S.

    2015-01-01

    This article presents an application of stress-constrained topology optimization to compliant mechanism design. An output displacement maximization formulation is used, together with the SIMP approach and a projection method to ensure convergence to nearly discrete designs. The maximum stress...... is approximated using a normalized version of the commonly-used p-norm of the effective von Mises stresses. The usual problems associated with topology optimization for compliant mechanism design: one-node and/or intermediate density hinges are alleviated by the stress constraint. However, it is also shown...

  17. Constrained Optimization and Optimal Control for Partial Differential Equations

    Leugering, Günter; Griewank, Andreas

    2012-01-01

    This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont

  18. Coevolutionary particle swarm optimization using Gaussian distribution for solving constrained optimization problems.

    Krohling, Renato A; Coelho, Leandro dos Santos

    2006-12-01

    In this correspondence, an approach based on coevolutionary particle swarm optimization to solve constrained optimization problems formulated as min-max problems is presented. In standard or canonical particle swarm optimization (PSO), a uniform probability distribution is used to generate random numbers for the accelerating coefficients of the local and global terms. We propose a Gaussian probability distribution to generate the accelerating coefficients of PSO. Two populations of PSO using Gaussian distribution are used on the optimization algorithm that is tested on a suite of well-known benchmark constrained optimization problems. Results have been compared with the canonical PSO (constriction factor) and with a coevolutionary genetic algorithm. Simulation results show the suitability of the proposed algorithm in terms of effectiveness and robustness.

  19. Optimization of chlorphenesin emulgel formulation

    Mohamed, Magdy I.

    2004-01-01

    This study was conducted to develop an emulgel formulation of chlorphenesin (CHL) using 2 types of gelling agents: hydroxypropylmethyl cellulose (HPMC) and Carbopol 934. The influence of the type of the gelling agent and the concentration of both the oil phase and emulsifying agent on the drug release from the prepared emulgels was investigated using a 23 factorial design. The prepared emulgels were evaluated for their physical appearance, rheological behavior, drug release, antifungal activi...

  20. Optimization of chlorphenesin emulgel formulation.

    Mohamed, Magdy I

    2004-10-11

    This study was conducted to develop an emulgel formulation of chlorphenesin (CHL) using 2 types of gelling agents: hydroxypropylmethyl cellulose (HPMC) and Carbopol 934. The influence of the type of the gelling agent and the concentration of both the oil phase and emulsifying agent on the drug release from the prepared emulgels was investigated using a 2(3) factorial design. The prepared emulgels were evaluated for their physical appearance, rheological behavior, drug release, antifungal activity, and stability. Commercially available CHL topical powder was used for comparison. All the prepared emulgels showed acceptable physical properties concerning color, homogeneity, consistency, spreadability, and pH value. They also exhibited higher drug release and antifungal activity than the CHL powder. It was found that the emulsifying agent concentration had the most pronounced effect on the drug release from the emulgels followed by the oil phase concentration and finally the type of the gelling agent. The drug release from all the emulgels was found to follow diffusion-controlled mechanism. Rheological studies revealed that the CHL emulgels exhibited a shear-thinning behavior with thixotropy. Stability studies showed that the physical appearance, rheological properties, drug release, and antifungal activity in all the prepared emulgels remained unchanged upon storage for 3 months. As a general conclusion, it was suggested that the CHL emulgel formulation prepared with HPMC with the oil phase concentration in its low level and emulsifying agent concentration in its high level was the formula of choice since it showed the highest drug release and antifungal activity.

  1. A model for optimal constrained adaptive testing

    van der Linden, Willem J.; Reese, Lynda M.

    2001-01-01

    A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

  2. A model for optimal constrained adaptive testing

    van der Linden, Willem J.; Reese, Lynda M.

    1997-01-01

    A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

  3. Chance constrained uncertain classification via robust optimization

    Ben-Tal, A.; Bhadra, S.; Bhattacharayya, C.; Saketha Nat, J.

    2011-01-01

    This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out

  4. Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems

    Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E

    2004-01-01

    .... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...

  5. Constrained Dynamic Optimality and Binomial Terminal Wealth

    Pedersen, J. L.; Peskir, G.

    2018-01-01

    with interest rate $r \\in {R}$). Letting $P_{t,x}$ denote a probability measure under which $X^u$ takes value $x$ at time $t,$ we study the dynamic version of the nonlinear optimal control problem $\\inf_u\\, Var{t,X_t^u}(X_T^u)$ where the infimum is taken over admissible controls $u$ subject to $X_t^u \\ge e...... a martingale method combined with Lagrange multipliers, we derive the dynamically optimal control $u_*^d$ in closed form and prove that the dynamically optimal terminal wealth $X_T^d$ can only take two values $g$ and $\\beta$. This binomial nature of the dynamically optimal strategy stands in sharp contrast...... with other known portfolio selection strategies encountered in the literature. A direct comparison shows that the dynamically optimal (time-consistent) strategy outperforms the statically optimal (time-inconsistent) strategy in the problem....

  6. [Optimization of formulations for dietetic pastry products].

    Villarroel, M; Uquiche, E; Brito, G; Cancino, M

    2000-03-01

    Optimized formulations of dietetic pastry products such as cake and sponge cake premixes were formulated using the surface response methodology. % Emulsifier agent and baking time were the selected independent variables for cake, as well as % emulsifier agent % chlorinated flour the variables selected for sponge cake. Three different level of each variable summing up thirteen experimental formulae of each product were assessed to optimize the variables that could have some influence in the sensory characteristics of these dietetic products. The total sensory quality was determined for both dietetic products using the composite scoring test and a panel of 18 trained judges. Looking at the contour graphic and considering economic aspects the best combination of variables for cake formulation was 2% emulsifier agent and 48 minutes for baking time, With respect to sponge cake, the best combination was 6% emulsifier agent and 48% chlorinated flour. Shelf life studies showed that both dietetic formulations remained stable during storage conditions of 75 days at 30 degrees C. During this period, significant differences in sensory characteristics were not found (p pastry products had good acceptability, and open up marketing opportunities for new products with potential health benefits to consumers.

  7. Constrained Optimization of MIMO Training Sequences

    Coon Justin P

    2007-01-01

    Full Text Available Multiple-input multiple-output (MIMO systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE, training sequences have been designed. However, in many practical systems it is not feasible to analytically find optimal solutions and numerical techniques must be used. In this paper, two systems (unique word (UW single carrier and OFDM with nulled subcarriers are considered and a method of designing near-optimal training sequences using nonlinear optimization techniques is proposed. In particular, interior-point (IP algorithms such as the barrier method are discussed. Although the two systems seem unrelated, the cost function, which is the MSE of the channel estimate, is shown to be effectively the same for each scenario. Also, additional constraints, such as peak-to-average power ratio (PAPR, are considered and shown to be easily included in the optimization process. Numerical examples illustrate the effectiveness of the designed training sequences, both in terms of MSE and bit-error rate (BER.

  8. Chance-constrained optimization of demand response to price signals

    Dorini, Gianluca Fabio; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    within a recursive least squares (RLS) framework using data measurable at the grid level, in an adaptive fashion. Optimal price signals are generated by embedding the FIR models within a chance-constrained optimization framework. The objective is to keep the price signal as unchanged as possible from...

  9. Effective Teaching of Economics: A Constrained Optimization Problem?

    Hultberg, Patrik T.; Calonge, David Santandreu

    2017-01-01

    One of the fundamental tenets of economics is that decisions are often the result of optimization problems subject to resource constraints. Consumers optimize utility, subject to constraints imposed by prices and income. As economics faculty, instructors attempt to maximize student learning while being constrained by their own and students'…

  10. Sequential unconstrained minimization algorithms for constrained optimization

    Byrne, Charles

    2008-01-01

    The problem of minimizing a function f(x):R J → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G k (x)=f(x)+g k (x), to obtain x k . The auxiliary functions g k (x):D subset of R J → R + are nonnegative on the set D, each x k is assumed to lie within D, and the objective is to minimize the continuous function f:R J → R over x in the set C = D-bar, the closure of D. We assume that such minimizers exist, and denote one such by x-circumflex. We assume that the functions g k (x) satisfy the inequalities 0≤g k (x)≤G k-1 (x)-G k-1 (x k-1 ), for k = 2, 3, .... Using this assumption, we show that the sequence {(x k )} is decreasing and converges to f(x-circumflex). If the restriction of f(x) to D has bounded level sets, which happens if x-circumflex is unique and f(x) is closed, proper and convex, then the sequence {x k } is bounded, and f(x*)=f(x-circumflex), for any cluster point x*. Therefore, if x-circumflex is unique, x* = x-circumflex and {x k } → x-circumflex. When x-circumflex is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results

  11. New Exact Penalty Functions for Nonlinear Constrained Optimization Problems

    Bingzhuang Liu

    2014-01-01

    Full Text Available For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.

  12. Constrained ripple optimization of Tokamak bundle divertors

    Hively, L.M.; Rome, J.A.; Lynch, V.E.; Lyon, J.F.; Fowler, R.H.; Peng, Y-K.M.; Dory, R.A.

    1983-02-01

    Magnetic field ripple from a tokamak bundle divertor is localized to a small toroidal sector and must be treated differently from the usual (distributed) toroidal field (TF) coil ripple. Generally, in a tokamak with an unoptimized divertor design, all of the banana-trapped fast ions are quickly lost due to banana drift diffusion or to trapping between the 1/R variation in absolute value vector B ω B and local field maxima due to the divertor. A computer code has been written to optimize automatically on-axis ripple subject to these constraints, while varying up to nine design parameters. Optimum configurations have low on-axis ripple ( 0 ) are lost. However, because finite-sized TF coils have not been used in this study, the flux bundle is not expanded

  13. Constrained optimization of test intervals using a steady-state genetic algorithm

    Martorell, S.; Carlos, S.; Sanchez, A.; Serradell, V.

    2000-01-01

    There is a growing interest from both the regulatory authorities and the nuclear industry to stimulate the use of Probabilistic Risk Analysis (PRA) for risk-informed applications at Nuclear Power Plants (NPPs). Nowadays, special attention is being paid on analyzing plant-specific changes to Test Intervals (TIs) within the Technical Specifications (TSs) of NPPs and it seems to be a consensus on the need of making these requirements more risk-effective and less costly. Resource versus risk-control effectiveness principles formally enters in optimization problems. This paper presents an approach for using the PRA models in conducting the constrained optimization of TIs based on a steady-state genetic algorithm (SSGA) where the cost or the burden is to be minimized while the risk or performance is constrained to be at a given level, or vice versa. The paper encompasses first with the problem formulation, where the objective function and constraints that apply in the constrained optimization of TIs based on risk and cost models at system level are derived. Next, the foundation of the optimizer is given, which is derived by customizing a SSGA in order to allow optimizing TIs under constraints. Also, a case study is performed using this approach, which shows the benefits of adopting both PRA models and genetic algorithms, in particular for the constrained optimization of TIs, although it is also expected a great benefit of using this approach to solve other engineering optimization problems. However, care must be taken in using genetic algorithms in constrained optimization problems as it is concluded in this paper

  14. Security constrained optimal power flow by modern optimization tools

    The main objective of an optimal power flow (OPF) functions is to optimize .... It is characterized as propagation of plants and this happens by gametes union. ... ss and different variables, for example, wind, nearby fertilization can have a critic.

  15. Optimal Power Constrained Distributed Detection over a Noisy Multiaccess Channel

    Zhiwen Hu

    2015-01-01

    Full Text Available The problem of optimal power constrained distributed detection over a noisy multiaccess channel (MAC is addressed. Under local power constraints, we define the transformation function for sensor to realize the mapping from local decision to transmitted waveform. The deflection coefficient maximization (DCM is used to optimize the performance of power constrained fusion system. Using optimality conditions, we derive the closed-form solution to the considered problem. Monte Carlo simulations are carried out to evaluate the performance of the proposed new method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system with low signal-to-noise ratio (SNR. We also show that the proposed new method has a robust detection performance for broad SNR region.

  16. Gravitational waves in Fully Constrained Formulation in a dynamical spacetime with matter content

    Cordero-Carrion, Isabel; Cerda-Duran, Pablo [Max-Planck-Institut fuer Astrophysik, Karl-Schwarzschild-Str. 1, D-85741, Garching (Germany); Ibanez, Jose MarIa, E-mail: chabela@mpa-garching.mpg.de, E-mail: cerda@mpa-garching.mpg.de, E-mail: jose.m.ibanez@uv.es [Departamento de AstronomIa y Astrofisica, Universidad de Valencia, C/ Dr. Moliner 50, E-46100 Burjassot, Valencia (Spain)

    2011-09-22

    We analyze numerically the behaviour of the hyperbolic sector of the Fully Constrained Formulation (FCF) (Bonazzola et al. 2004). The numerical experiments allow us to be confident in the performances of the upgraded version of the CoCoNuT code (Dimmelmeier et al. 2005) by replacing the Conformally Flat Condition (CFC), an approximation of Einstein equations, by FCF. First gravitational waves in FCF in a dynamical spacetime with matter content will be shown.

  17. Quasicanonical structure of optimal control in constrained discrete systems

    Sieniutycz, S.

    2003-06-01

    This paper considers discrete processes governed by difference rather than differential equations for the state transformation. The basic question asked is if and when Hamiltonian canonical structures are possible in optimal discrete systems. Considering constrained discrete control, general optimization algorithms are derived that constitute suitable theoretical and computational tools when evaluating extremum properties of constrained physical models. The mathematical basis of the general theory is the Bellman method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage criterion which allows a variation of the terminal state that is otherwise fixed in the Bellman's method. Two relatively unknown, powerful optimization algorithms are obtained: an unconventional discrete formalism of optimization based on a Hamiltonian for multistage systems with unconstrained intervals of holdup time, and the time interval constrained extension of the formalism. These results are general; namely, one arrives at: the discrete canonical Hamilton equations, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory along with all basic results of variational calculus. Vast spectrum of applications of the theory is briefly discussed.

  18. A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization

    Zhijun Luo

    2014-01-01

    Full Text Available A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved.

  19. Superalloy design - A Monte Carlo constrained optimization method

    Stander, CM

    1996-01-01

    Full Text Available optimization method C. M. Stander Division of Materials Science and Technology, CSIR, PO Box 395, Pretoria, Republic of South Africa Received 74 March 1996; accepted 24 June 1996 A method, based on Monte Carlo constrained... successful hit, i.e. when Liow < LMP,,, < Lhiph, and for all the properties, Pj?, < P, < Pi@?. If successful this hit falls within the ROA. Repeat steps 4 and 5 to find at least ten (or more) successful hits with values...

  20. Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers

    Adam, Lukáš; Branda, Martin

    2016-01-01

    Roč. 170, č. 2 (2016), s. 419-436 ISSN 0022-3239 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Chance constrained programming * Optimality conditions * Regularization * Algorithms * Free MATLAB codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.289, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0460909.pdf

  1. A penalty method for PDE-constrained optimization in inverse problems

    Leeuwen, T van; Herrmann, F J

    2016-01-01

    Many inverse and parameter estimation problems can be written as PDE-constrained optimization problems. The goal is to infer the parameters, typically coefficients of the PDE, from partial measurements of the solutions of the PDE for several right-hand sides. Such PDE-constrained problems can be solved by finding a stationary point of the Lagrangian, which entails simultaneously updating the parameters and the (adjoint) state variables. For large-scale problems, such an all-at-once approach is not feasible as it requires storing all the state variables. In this case one usually resorts to a reduced approach where the constraints are explicitly eliminated (at each iteration) by solving the PDEs. These two approaches, and variations thereof, are the main workhorses for solving PDE-constrained optimization problems arising from inverse problems. In this paper, we present an alternative method that aims to combine the advantages of both approaches. Our method is based on a quadratic penalty formulation of the constrained optimization problem. By eliminating the state variable, we develop an efficient algorithm that has roughly the same computational complexity as the conventional reduced approach while exploiting a larger search space. Numerical results show that this method indeed reduces some of the nonlinearity of the problem and is less sensitive to the initial iterate. (paper)

  2. Constrained multi-objective optimization of storage ring lattices

    Husain, Riyasat; Ghodke, A. D.

    2018-03-01

    The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

  3. Thermally-Constrained Fuel-Optimal ISS Maneuvers

    Bhatt, Sagar; Svecz, Andrew; Alaniz, Abran; Jang, Jiann-Woei; Nguyen, Louis; Spanos, Pol

    2015-01-01

    Optimal Propellant Maneuvers (OPMs) are now being used to rotate the International Space Station (ISS) and have saved hundreds of kilograms of propellant over the last two years. The savings are achieved by commanding the ISS to follow a pre-planned attitude trajectory optimized to take advantage of environmental torques. The trajectory is obtained by solving an optimal control problem. Prior to use on orbit, OPM trajectories are screened to ensure a static sun vector (SSV) does not occur during the maneuver. The SSV is an indicator that the ISS hardware temperatures may exceed thermal limits, causing damage to the components. In this paper, thermally-constrained fuel-optimal trajectories are presented that avoid an SSV and can be used throughout the year while still reducing propellant consumption significantly.

  4. Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

    Weishang Gao

    2013-01-01

    Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.

  5. Constrained Burn Optimization for the International Space Station

    Brown, Aaron J.; Jones, Brandon A.

    2017-01-01

    In long-term trajectory planning for the International Space Station (ISS), translational burns are currently targeted sequentially to meet the immediate trajectory constraints, rather than simultaneously to meet all constraints, do not employ gradient-based search techniques, and are not optimized for a minimum total deltav (v) solution. An analytic formulation of the constraint gradients is developed and used in an optimization solver to overcome these obstacles. Two trajectory examples are explored, highlighting the advantage of the proposed method over the current approach, as well as the potential v and propellant savings in the event of propellant shortages.

  6. Adaptive Multi-Agent Systems for Constrained Optimization

    Macready, William; Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

  7. Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

    Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto

    2018-01-12

    This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

  8. Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

    Liyang Wang

    2017-01-01

    Full Text Available The application of biped robots is always trapped by their high energy consumption. This paper makes a contribution by optimizing the joint torques to decrease the energy consumption without changing the biped gaits. In this work, a constrained quadratic programming (QP problem for energy optimization is formulated. A neurodynamics-based solver is presented to solve the QP problem. Differing from the existing literatures, the proposed neurodynamics-based energy optimization (NEO strategy minimizes the energy consumption and guarantees the following three important constraints simultaneously: (i the force-moment equilibrium equation of biped robots, (ii frictions applied by each leg on the ground to hold the biped robot without slippage and tipping over, and (iii physical limits of the motors. Simulations demonstrate that the proposed strategy is effective for energy-efficient biped walking.

  9. Fast optimization of statistical potentials for structurally constrained phylogenetic models

    Rodrigue Nicolas

    2009-09-01

    Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.

  10. Formulation Optimization and In-vitro Evaluation of Oral Floating ...

    matrix tablets and to systematically optimize its drug release using varying levels of xanthan gum and hydroxypropyl ... stomach and improve oral bioavailability of drugs that have ... which can affect its sustained release formulation. [19].

  11. Improved Sensitivity Relations in State Constrained Optimal Control

    Bettiol, Piernicola; Frankowska, Hélène; Vinter, Richard B.

    2015-01-01

    Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because

  12. Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

    R. Manam

    2017-12-01

    Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

  13. Formulation of optimal international freight transport objective

    A. Jarašūnienė

    2002-10-01

    Full Text Available To increase the attraction of Lithuania as a transit country striving to promote carriers' border crossing activities and facilitate customs clearance procedures as well as freight delivery to clients it is necessary to identify the main obstacles, to analyse them and to select adequate measures and means for their elimination. Therefore, on the basis of the formulation of transport freight management objective, as well as basing on the assessment of indeterminacy of external impacts, it would be possible to deduce the main causes of idle time of transport means in customs, to estimate the dependence of service time in proportion to transport flow.

  14. Pareto-optimal estimates that constrain mean California precipitation change

    Langenbrunner, B.; Neelin, J. D.

    2017-12-01

    Global climate model (GCM) projections of greenhouse gas-induced precipitation change can exhibit notable uncertainty at the regional scale, particularly in regions where the mean change is small compared to internal variability. This is especially true for California, which is located in a transition zone between robust precipitation increases to the north and decreases to the south, and where GCMs from the Climate Model Intercomparison Project phase 5 (CMIP5) archive show no consensus on mean change (in either magnitude or sign) across the central and southern parts of the state. With the goal of constraining this uncertainty, we apply a multiobjective approach to a large set of subensembles (subsets of models from the full CMIP5 ensemble). These constraints are based on subensemble performance in three fields important to California precipitation: tropical Pacific sea surface temperatures, upper-level zonal winds in the midlatitude Pacific, and precipitation over the state. An evolutionary algorithm is used to sort through and identify the set of Pareto-optimal subensembles across these three measures in the historical climatology, and we use this information to constrain end-of-century California wet season precipitation change. This technique narrows the range of projections throughout the state and increases confidence in estimates of positive mean change. Furthermore, these methods complement and generalize emergent constraint approaches that aim to restrict uncertainty in end-of-century projections, and they have applications to even broader aspects of uncertainty quantification, including parameter sensitivity and model calibration.

  15. Block-triangular preconditioners for PDE-constrained optimization

    Rees, Tyrone; Stoll, Martin

    2010-01-01

    In this paper we investigate the possibility of using a block-triangular preconditioner for saddle point problems arising in PDE-constrained optimization. In particular, we focus on a conjugate gradient-type method introduced by Bramble and Pasciak that uses self-adjointness of the preconditioned system in a non-standard inner product. We show when the Chebyshev semi-iteration is used as a preconditioner for the relevant matrix blocks involving the finite element mass matrix that the main drawback of the Bramble-Pasciak method-the appropriate scaling of the preconditioners-is easily overcome. We present an eigenvalue analysis for the block-triangular preconditioners that gives convergence bounds in the non-standard inner product and illustrates their competitiveness on a number of computed examples. Copyright © 2010 John Wiley & Sons, Ltd.

  16. Block-triangular preconditioners for PDE-constrained optimization

    Rees, Tyrone

    2010-11-26

    In this paper we investigate the possibility of using a block-triangular preconditioner for saddle point problems arising in PDE-constrained optimization. In particular, we focus on a conjugate gradient-type method introduced by Bramble and Pasciak that uses self-adjointness of the preconditioned system in a non-standard inner product. We show when the Chebyshev semi-iteration is used as a preconditioner for the relevant matrix blocks involving the finite element mass matrix that the main drawback of the Bramble-Pasciak method-the appropriate scaling of the preconditioners-is easily overcome. We present an eigenvalue analysis for the block-triangular preconditioners that gives convergence bounds in the non-standard inner product and illustrates their competitiveness on a number of computed examples. Copyright © 2010 John Wiley & Sons, Ltd.

  17. Optimal dispatch in dynamic security constrained open power market

    Singh, S.N.; David, A.K.

    2002-01-01

    Power system security is a new concern in the competitive power market operation, because the integration of the system controller and the generation owner has been broken. This paper presents an approach for dynamic security constrained optimal dispatch in restructured power market environment. The transient energy margin using transient energy function (TEF) approach has been used to calculate the stability margin of the system and a hybrid method is applied to calculate the approximate unstable equilibrium point (UEP) that is used to calculate the exact UEP and thus, the energy margin using TEF. The case study results illustrated on two systems shows that the operating mechanisms are compatible with the new business environment. (author)

  18. A New Interpolation Approach for Linearly Constrained Convex Optimization

    Espinoza, Francisco

    2012-08-01

    In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard\\'s interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton\\'s method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.

  19. Topology Optimization for Minimizing the Resonant Response of Plates with Constrained Layer Damping Treatment

    Zhanpeng Fang

    2015-01-01

    Full Text Available A topology optimization method is proposed to minimize the resonant response of plates with constrained layer damping (CLD treatment under specified broadband harmonic excitations. The topology optimization problem is formulated and the square of displacement resonant response in frequency domain at the specified point is considered as the objective function. Two sensitivity analysis methods are investigated and discussed. The derivative of modal damp ratio is not considered in the conventional sensitivity analysis method. An improved sensitivity analysis method considering the derivative of modal damp ratio is developed to improve the computational accuracy of the sensitivity. The evolutionary structural optimization (ESO method is used to search the optimal layout of CLD material on plates. Numerical examples and experimental results show that the optimal layout of CLD treatment on the plate from the proposed topology optimization using the conventional sensitivity analysis or the improved sensitivity analysis can reduce the displacement resonant response. However, the optimization method using the improved sensitivity analysis can produce a higher modal damping ratio than that using the conventional sensitivity analysis and develop a smaller displacement resonant response.

  20. A simple two stage optimization algorithm for constrained power economic dispatch

    Huang, G.; Song, K.

    1994-01-01

    A simple two stage optimization algorithm is proposed and investigated for fast computation of constrained power economic dispatch control problems. The method is a simple demonstration of the hierarchical aggregation-disaggregation (HAD) concept. The algorithm first solves an aggregated problem to obtain an initial solution. This aggregated problem turns out to be classical economic dispatch formulation, and it can be solved in 1% of overall computation time. In the second stage, linear programming method finds optimal solution which satisfies power balance constraints, generation and transmission inequality constraints and security constraints. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that the two stage method obtains average speedup ratio 10.64 as compared to classical LP-based method

  1. A constrained multinomial Probit route choice model in the metro network: Formulation, estimation and application

    Zhang, Yongsheng; Wei, Heng; Zheng, Kangning

    2017-01-01

    Considering that metro network expansion brings us with more alternative routes, it is attractive to integrate the impacts of routes set and the interdependency among alternative routes on route choice probability into route choice modeling. Therefore, the formulation, estimation and application of a constrained multinomial probit (CMNP) route choice model in the metro network are carried out in this paper. The utility function is formulated as three components: the compensatory component is a function of influencing factors; the non-compensatory component measures the impacts of routes set on utility; following a multivariate normal distribution, the covariance of error component is structured into three parts, representing the correlation among routes, the transfer variance of route, and the unobserved variance respectively. Considering multidimensional integrals of the multivariate normal probability density function, the CMNP model is rewritten as Hierarchical Bayes formula and M-H sampling algorithm based Monte Carlo Markov Chain approach is constructed to estimate all parameters. Based on Guangzhou Metro data, reliable estimation results are gained. Furthermore, the proposed CMNP model also shows a good forecasting performance for the route choice probabilities calculation and a good application performance for transfer flow volume prediction. PMID:28591188

  2. Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics

    Xi Wang

    2016-01-01

    Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.

  3. PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

    Sen, Satyabrata [ORNL

    2014-01-01

    We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratio (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.

  4. Electrochemomechanical constrained multiobjective optimization of PPy/MWCNT actuators

    Khalili, N; Naguib, H E; Kwon, R H

    2014-01-01

    Polypyrrole (PPy) conducting polymers have shown a great potential for the fabrication of conjugated polymer-based actuating devices. Consequently, they have been a key point in developing many advanced emerging applications such as biomedical devices and biomimetic robotics. When designing an actuator, taking all of the related decision variables, their roles and relationships into consideration is of pivotal importance to determine the actuator’s final performance. Therefore, the central focus of this study is to develop an electrochemomechanical constrained multiobjective optimization model of a PPy/MWCNTs trilayer actuator. For this purpose, the objective functions are designed to capture the three main characteristics of these actuators, namely their tip vertical displacement, blocking force and response time. To obtain the optimum range of the designated decision variables within the feasible domain, a multiobjective optimization algorithm is applied while appropriate constraints are imposed. The optimum points form a Pareto surface on which they are consistently spread. The numerical results are presented; these results enable one to design an actuator with consideration to the desired output performances. For the experimental analysis, a multilayer bending-type actuator is fabricated, which is composed of a PVDF layer and two layers of PPy with an incorporated layer of multi-walled carbon nanotubes deposited on each side of the PVDF membrane. The numerical results are experimentally verified; in order to determine the performance of the fabricated actuator, its outputs are compared with a neat PPy actuator’s experimental and numerical counterparts. (paper)

  5. Solution for state constrained optimal control problems applied to power split control for hybrid vehicles

    Keulen, van T.A.C.; Gillot, J.; Jager, de A.G.; Steinbuch, M.

    2014-01-01

    This paper presents a numerical solution for scalar state constrained optimal control problems. The algorithm rewrites the constrained optimal control problem as a sequence of unconstrained optimal control problems which can be solved recursively as a two point boundary value problem. The solution

  6. [Formulation optimization of panax notoginsenoside orally fast disintegration tablets].

    Wang, Zhi; Wei, Li; Chen, Ting

    2008-07-01

    To optimize the formulation of panax notoginsenoside orally fast disintegrating tablets. Mannitol, microcrystalline cellulose (PH 102) and lactose 80 were used as diluent. A polynomial regression algorithm was used to evaluate the relationship between the controlling factor, compacting pressure and diluent ratio, and disintegration time, tensile strength of tablets. Optimum formulation and process parameters could be determined by contrast the contour plot of tensile strength to that of disintegration time. The disintegration time and tensile strength of panax notoginsenoside oral disintegrating tablets were good, and the taste was satisfactory. Panax notoginsenoside oral disintegrating tablets achieve the goal of design and this method can be fairly used in formulation screening.

  7. Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

    Xiaogang Guo

    2018-01-01

    Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

  8. Optimization and characterization of liposome formulation by mixture design.

    Maherani, Behnoush; Arab-tehrany, Elmira; Kheirolomoom, Azadeh; Reshetov, Vadzim; Stebe, Marie José; Linder, Michel

    2012-02-07

    This study presents the application of the mixture design technique to develop an optimal liposome formulation by using the different lipids in type and percentage (DOPC, POPC and DPPC) in liposome composition. Ten lipid mixtures were generated by the simplex-centroid design technique and liposomes were prepared by the extrusion method. Liposomes were characterized with respect to size, phase transition temperature, ζ-potential, lamellarity, fluidity and efficiency in loading calcein. The results were then applied to estimate the coefficients of mixture design model and to find the optimal lipid composition with improved entrapment efficiency, size, transition temperature, fluidity and ζ-potential of liposomes. The response optimization of experiments was the liposome formulation with DOPC: 46%, POPC: 12% and DPPC: 42%. The optimal liposome formulation had an average diameter of 127.5 nm, a phase-transition temperature of 11.43 °C, a ζ-potential of -7.24 mV, fluidity (1/P)(TMA-DPH)((¬)) value of 2.87 and an encapsulation efficiency of 20.24%. The experimental results of characterization of optimal liposome formulation were in good agreement with those predicted by the mixture design technique.

  9. A constrained maximization formulation to analyze deformation of fiber reinforced elastomeric actuators

    Singh, Gaurav; Krishnan, Girish

    2017-06-01

    Fiber reinforced elastomeric enclosures (FREEs) are soft and smart pneumatic actuators that deform in a predetermined fashion upon inflation. This paper analyzes the deformation behavior of FREEs by formulating a simple calculus of variations problem that involves constrained maximization of the enclosed volume. The model accurately captures the deformed shape for FREEs with any general fiber angle orientation, and its relation with actuation pressure, material properties and applied load. First, the accuracy of the model is verified with existing literature and experiments for the popular McKibben pneumatic artificial muscle actuator with two equal and opposite families of helically wrapped fibers. Then, the model is used to predict and experimentally validate the deformation behavior of novel rotating-contracting FREEs, for which no prior literature exist. The generality of the model enables conceptualization of novel FREEs whose fiber orientations vary arbitrarily along the geometry. Furthermore, the model is deemed to be useful in the design synthesis of fiber reinforced elastomeric actuators for general axisymmetric desired motion and output force requirement.

  10. Amodified probabilistic genetic algorithm for the solution of complex constrained optimization problems

    Vorozheikin, A.; Gonchar, T.; Panfilov, I.; Sopov, E.; Sopov, S.

    2009-01-01

    A new algorithm for the solution of complex constrained optimization problems based on the probabilistic genetic algorithm with optimal solution prediction is proposed. The efficiency investigation results in comparison with standard genetic algorithm are presented.

  11. Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

    Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

    2002-06-01

    This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

  12. Depletion mapping and constrained optimization to support managing groundwater extraction

    Fienen, Michael N.; Bradbury, Kenneth R.; Kniffin, Maribeth; Barlow, Paul M.

    2018-01-01

    Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping—showing the model-calculated potential impacts that wells have on stream baseflow—can form the basis for multiple potential management approaches in an oversubscribed basin. Specific management approaches can include scenarios proposed by stakeholders, systematic changes in well pumping based on depletion potential, and formal constrained optimization, which can be used to quantify the tradeoff between water use and stream baseflow. Variables such as the maximum amount of reduction allowed in each well and various groupings of wells using, for example, K-means clustering considering spatial proximity and depletion potential are considered. These approaches provide a potential starting point and guidance for resource managers and stakeholders to make decisions about groundwater management in a basin, spreading responsibility in different ways. We illustrate these approaches in the Little Plover River basin in central Wisconsin, United States—home to a rich agricultural tradition, with farmland and urban areas both in close proximity to a groundwater-dependent trout stream. Groundwater withdrawals have reduced baseflow supplying the Little Plover River below a legally established minimum. The techniques in this work were developed in response to engaged stakeholders with various interests and goals for the basin. They sought to develop a collaborative management plan at a watershed scale that restores the flow rate in the river in a manner that incorporates principles of shared governance and results in effective and minimally disruptive changes in groundwater extraction practices.

  13. Optimized formulation of solid self-microemulsifying sirolimus delivery systems

    Cho W

    2013-04-01

    Full Text Available Wonkyung Cho,1,2 Min-Soo Kim,3 Jeong-Soo Kim,2 Junsung Park,1,2 Hee Jun Park,1,2 Kwang-Ho Cha,1,2 Jeong-Sook Park,2 Sung-Joo Hwang1,4 1Yonsei Institute of Pharmaceutical Sciences, Yonsei University, Incheon, Republic of Korea; 2College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea; 3Department of Pharmaceutical Engineering, Inje University, Gimhae, Republic of Korea; 4College of Pharmacy, Yonsei University, Incheon, Republic of Korea Background: The aim of this study was to develop an optimized solid self-microemulsifying drug delivery system (SMEDDS formulation for sirolimus to enhance its solubility, stability, and bioavailability. Methods: Excipients used for enhancing the solubility and stability of sirolimus were screened. A phase-separation test, visual observation for emulsifying efficiency, and droplet size analysis were performed. Ternary phase diagrams were constructed to optimize the liquid SMEDDS formulation. The selected liquid SMEDDS formulations were prepared into solid form. The dissolution profiles and pharmacokinetic profiles in rats were analyzed. Results: In the results of the oil and cosolvent screening studies, Capryol™ Propylene glycol monocaprylate (PGMC and glycofurol exhibited the highest solubility of all oils and cosolvents, respectively. In the surfactant screening test, D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS was determined to be the most effective stabilizer of sirolimus in pH 1.2 simulated gastric fluids. The optimal formulation determined by the construction of ternary phase diagrams was the T32 (Capryol™ PGMC:glycofurol:vitamin E TPGS = 30:30:40 weight ratio formulation with a mean droplet size of 108.2 ± 11.4 nm. The solid SMEDDS formulations were prepared with Sucroester 15 and mannitol. The droplet size of the reconstituted solid SMEDDS showed no significant difference compared with the liquid SMEDDS. In the dissolution study, the release amounts of

  14. Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

    Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

    2016-01-01

    In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

  15. A novel constrained H2 optimization algorithm for mechatronics design in flexure-linked biaxial gantry.

    Ma, Jun; Chen, Si-Lu; Kamaldin, Nazir; Teo, Chek Sing; Tay, Arthur; Mamun, Abdullah Al; Tan, Kok Kiong

    2017-11-01

    The biaxial gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers from breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a flexure-linked biaxial gantry is designed to allow a small rotation angle of the cross-arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end-effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-to-point reference trajectories with same dynamics but different steps. From here, an H 2 optimization problem with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal step. Comparative experimental results obtained on the testbed are presented to verify the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

    Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

    2017-06-01

    Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

  17. Convex Relaxations of Chance Constrained AC Optimal Power Flow

    Venzke, Andreas; Halilbasic, Lejla; Markovic, Uros

    2017-01-01

    , reactive power, and voltage. We state a tractable formulation for two types of uncertainty sets. Using a scenario-based approach and making no prior assumptions about the probability distribution of the forecast errors, we obtain a robust formulation for a rectangular uncertainty set. Alternatively...

  18. An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems

    Vivek Patel

    2012-08-01

    Full Text Available Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.

  19. Selection of magnetorheological brake types via optimal design considering maximum torque and constrained volume

    Nguyen, Q H; Choi, S B

    2012-01-01

    This research focuses on optimal design of different types of magnetorheological brakes (MRBs), from which an optimal selection of MRB types is identified. In the optimization, common types of MRB such as disc-type, drum-type, hybrid-types, and T-shaped type are considered. The optimization problem is to find the optimal value of significant geometric dimensions of the MRB that can produce a maximum braking torque. The MRB is constrained in a cylindrical volume of a specific radius and length. After a brief description of the configuration of MRB types, the braking torques of the MRBs are derived based on the Herschel–Bulkley model of the MR fluid. The optimal design of MRBs constrained in a specific cylindrical volume is then analysed. The objective of the optimization is to maximize the braking torque while the torque ratio (the ratio of maximum braking torque and the zero-field friction torque) is constrained to be greater than a certain value. A finite element analysis integrated with an optimization tool is employed to obtain optimal solutions of the MRBs. Optimal solutions of MRBs constrained in different volumes are obtained based on the proposed optimization procedure. From the results, discussions on the optimal selection of MRB types depending on constrained volumes are given. (paper)

  20. On projection methods, convergence and robust formulations in topology optimization

    Wang, Fengwen; Lazarov, Boyan Stefanov; Sigmund, Ole

    2011-01-01

    alleviated using various projection methods. In this paper we show that simple projection methods do not ensure local mesh-convergence and propose a modified robust topology optimization formulation based on erosion, intermediate and dilation projections that ensures both global and local mesh-convergence.......Mesh convergence and manufacturability of topology optimized designs have previously mainly been assured using density or sensitivity based filtering techniques. The drawback of these techniques has been gray transition regions between solid and void parts, but this problem has recently been...

  1. Fuzzy chance constrained linear programming model for scrap charge optimization in steel production

    Rong, Aiying; Lahdelma, Risto

    2008-01-01

    the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...

  2. Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems

    Hailong Wang

    2018-01-01

    Full Text Available The backtracking search optimization algorithm (BSA is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.

  3. A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

    Biwei Tang

    2016-01-01

    Full Text Available This paper develops a particle swarm optimization (PSO based framework for constrained optimization problems (COPs. Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011 algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs.

  4. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  5. A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization.

    Qin, Sitian; Feng, Jiqiang; Song, Jiahui; Wen, Xingnan; Xu, Chen

    2018-03-01

    In this paper, based on calculus and penalty method, a one-layer recurrent neural network is proposed for solving constrained complex-variable convex optimization. It is proved that for any initial point from a given domain, the state of the proposed neural network reaches the feasible region in finite time and converges to an optimal solution of the constrained complex-variable convex optimization finally. In contrast to existing neural networks for complex-variable convex optimization, the proposed neural network has a lower model complexity and better convergence. Some numerical examples and application are presented to substantiate the effectiveness of the proposed neural network.

  6. Dynamical computation of constrained flexible systems using a modal Udwadia-Kalaba formulation: Application to musical instruments.

    Antunes, J; Debut, V

    2017-02-01

    Most musical instruments consist of dynamical subsystems connected at a number of constraining points through which energy flows. For physical sound synthesis, one important difficulty deals with enforcing these coupling constraints. While standard techniques include the use of Lagrange multipliers or penalty methods, in this paper, a different approach is explored, the Udwadia-Kalaba (U-K) formulation, which is rooted on analytical dynamics but avoids the use of Lagrange multipliers. This general and elegant formulation has been nearly exclusively used for conceptual systems of discrete masses or articulated rigid bodies, namely, in robotics. However its natural extension to deal with continuous flexible systems is surprisingly absent from the literature. Here, such a modeling strategy is developed and the potential of combining the U-K equation for constrained systems with the modal description is shown, in particular, to simulate musical instruments. Objectives are twofold: (1) Develop the U-K equation for constrained flexible systems with subsystems modelled through unconstrained modes; and (2) apply this framework to compute string/body coupled dynamics. This example complements previous work [Debut, Antunes, Marques, and Carvalho, Appl. Acoust. 108, 3-18 (2016)] on guitar modeling using penalty methods. Simulations show that the proposed technique provides similar results with a significant improvement in computational efficiency.

  7. Constraining neutron guide optimizations with phase-space considerations

    Bertelsen, Mads, E-mail: mads.bertelsen@gmail.com; Lefmann, Kim

    2016-09-11

    We introduce a method named the Minimalist Principle that serves to reduce the parameter space for neutron guide optimization when the required beam divergence is limited. The reduced parameter space will restrict the optimization to guides with a minimal neutron intake that are still theoretically able to deliver the maximal possible performance. The geometrical constraints are derived using phase-space propagation from moderator to guide and from guide to sample, while assuming that the optimized guides will achieve perfect transport of the limited neutron intake. Guide systems optimized using these constraints are shown to provide performance close to guides optimized without any constraints, however the divergence received at the sample is limited to the desired interval, even when the neutron transport is not limited by the supermirrors used in the guide. As the constraints strongly limit the parameter space for the optimizer, two control parameters are introduced that can be used to adjust the selected subspace, effectively balancing between maximizing neutron transport and avoiding background from unnecessary neutrons. One parameter is needed to describe the expected focusing abilities of the guide to be optimized, going from perfectly focusing to no correlation between position and velocity. The second parameter controls neutron intake into the guide, so that one can select exactly how aggressively the background should be limited. We show examples of guides optimized using these constraints which demonstrates the higher signal to noise than conventional optimizations. Furthermore the parameter controlling neutron intake is explored which shows that the simulated optimal neutron intake is close to the analytically predicted, when assuming that the guide is dominated by multiple scattering events.

  8. A constrained optimization algorithm for total energy minimization in electronic structure calculations

    Yang Chao; Meza, Juan C.; Wang Linwang

    2006-01-01

    A new direct constrained optimization algorithm for minimizing the Kohn-Sham (KS) total energy functional is presented in this paper. The key ingredients of this algorithm involve projecting the total energy functional into a sequence of subspaces of small dimensions and seeking the minimizer of total energy functional within each subspace. The minimizer of a subspace energy functional not only provides a search direction along which the KS total energy functional decreases but also gives an optimal 'step-length' to move along this search direction. Numerical examples are provided to demonstrate that this new direct constrained optimization algorithm can be more efficient than the self-consistent field (SCF) iteration

  9. Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

    Steinley, Douglas; Hubert, Lawrence

    2008-01-01

    This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…

  10. Constrained optimal motion planning for autonomous vehicles using PRONTO

    Aguiar, A.P.; Bayer, F.A.; Hauser, J.; Häusler, A.J.; Notarstefano, G.; Pascoal, A.M.; Rucco, A.; Saccon, A.

    2017-01-01

    This chapter provides an overview of the authors’ efforts in vehicle trajectory exploration and motion planning based on PRONTO, a numerical method for solving optimal control problems developed over the last two decades. The chapter reviews the basics of PRONTO, providing the appropriate references

  11. Human fetal growth is constrained below optimal for perinatal survival

    Vasak, B.; Koenen, S. V.; Koster, M. P. H.; Hukkelhoven, C. W. P. M.; Franx, A.; Hanson, M. A.; Visser, GHA

    ObjectiveThe use of fetal growth charts assumes that the optimal size at birth is at the 50(th) birth-weight centile, but interaction between maternal constraints on fetal growth and the risks associated with small and large fetal size at birth may indicate that this assumption is not valid for

  12. Efficient relaxations for joint chance constrained AC optimal power flow

    Baker, Kyri; Toomey, Bridget

    2017-07-01

    Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality as an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.

  13. Preconditioning for partial differential equation constrained optimization with control constraints

    Stoll, Martin; Wathen, Andy

    2011-01-01

    Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

  14. Preconditioning for partial differential equation constrained optimization with control constraints

    Stoll, Martin

    2011-10-18

    Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

  15. Kinetic Constrained Optimization of the Golf Swing Hub Path

    Steven M. Nesbit

    2014-12-01

    Full Text Available This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study.

  16. Constrained Fuzzy Predictive Control Using Particle Swarm Optimization

    Oussama Ait Sahed

    2015-01-01

    Full Text Available A fuzzy predictive controller using particle swarm optimization (PSO approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal computational time. This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. The efficiency of the proposed control algorithm is evaluated by considering the control of the model of a 4 × 4 Multi-Input Multi-Output industrial boiler. This model is characterized by being nonlinear with high interactions between its inputs and outputs, having a nonminimum phase behaviour, and containing instabilities and time delays. The obtained results are compared to those of the control algorithms based on the conventional PSO and the linear approach.

  17. Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

    Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

    with information to improve their crop's vigor has been a major topic of interest. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, the efficiency of farming must increase to meet future food requirements and to make farming a sustainable occupation for the farmer. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The goal is to increase farm revenue by increasing crop yield and decreasing applications of costly chemical and water treatments. In addition, this methodology will decrease the environmental costs of farming, i.e., reduce air, soil, and water pollution. Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now available. Commercial satellite systems can image (multi-spectral) the Earth with a resolution of approximately 2.5 m. Variable precision dispensing systems using GPS are available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been formulated. Personal computers and internet access are in place in most farm homes and can provide a mechanism to periodically disseminate, e.g. bi-weekly, advice on what quantities of water and chemicals are needed in individual regions of the field. What is missing is a model that fuses the disparate sources of information on the current states of the crop and soil, and the remaining resource levels available with the decisions farmers are required to make. This must be a product that is easy for the farmer to understand and to implement. A "Constrained Optimization Feed-back Control Model" to fill this void will be presented. The objective function of the model will be used to maximize the farmer's profit by increasing yields while decreasing environmental costs and decreasing

  18. Topology Optimization of Constrained Layer Damping on Plates Using Method of Moving Asymptote (MMA Approach

    Zheng Ling

    2011-01-01

    Full Text Available Damping treatments have been extensively used as a powerful means to damp out structural resonant vibrations. Usually, damping materials are fully covered on the surface of plates. The drawbacks of this conventional treatment are also obvious due to an added mass and excess material consumption. Therefore, it is not always economical and effective from an optimization design view. In this paper, a topology optimization approach is presented to maximize the modal damping ratio of the plate with constrained layer damping treatment. The governing equation of motion of the plate is derived on the basis of energy approach. A finite element model to describe dynamic performances of the plate is developed and used along with an optimization algorithm in order to determine the optimal topologies of constrained layer damping layout on the plate. The damping of visco-elastic layer is modeled by the complex modulus formula. Considering the vibration and energy dissipation mode of the plate with constrained layer damping treatment, damping material density and volume factor are considered as design variable and constraint respectively. Meantime, the modal damping ratio of the plate is assigned as the objective function in the topology optimization approach. The sensitivity of modal damping ratio to design variable is further derived and Method of Moving Asymptote (MMA is adopted to search the optimized topologies of constrained layer damping layout on the plate. Numerical examples are used to demonstrate the effectiveness of the proposed topology optimization approach. The results show that vibration energy dissipation of the plates can be enhanced by the optimal constrained layer damping layout. This optimal technology can be further extended to vibration attenuation of sandwich cylindrical shells which constitute the major building block of many critical structures such as cabins of aircrafts, hulls of submarines and bodies of rockets and missiles as an

  19. Kinetic constrained optimization of the golf swing hub path.

    Nesbit, Steven M; McGinnis, Ryan S

    2014-12-01

    This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key PointsThe hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer.It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer.It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories.Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact.The hand path trajectory has important influences over the club swing trajectory.

  20. A Simply Constrained Optimization Reformulation of KKT Systems Arising from Variational Inequalities

    Facchinei, F.; Fischer, A.; Kanzow, C.; Peng, J.-M.

    1999-01-01

    The Karush-Kuhn-Tucker (KKT) conditions can be regarded as optimality conditions for both variational inequalities and constrained optimization problems. In order to overcome some drawbacks of recently proposed reformulations of KKT systems, we propose casting KKT systems as a minimization problem with nonnegativity constraints on some of the variables. We prove that, under fairly mild assumptions, every stationary point of this constrained minimization problem is a solution of the KKT conditions. Based on this reformulation, a new algorithm for the solution of the KKT conditions is suggested and shown to have some strong global and local convergence properties

  1. A one-layer recurrent neural network for constrained nonsmooth invex optimization.

    Li, Guocheng; Yan, Zheng; Wang, Jun

    2014-02-01

    Invexity is an important notion in nonconvex optimization. In this paper, a one-layer recurrent neural network is proposed for solving constrained nonsmooth invex optimization problems, designed based on an exact penalty function method. It is proved herein that any state of the proposed neural network is globally convergent to the optimal solution set of constrained invex optimization problems, with a sufficiently large penalty parameter. In addition, any neural state is globally convergent to the unique optimal solution, provided that the objective function and constraint functions are pseudoconvex. Moreover, any neural state is globally convergent to the feasible region in finite time and stays there thereafter. The lower bounds of the penalty parameter and convergence time are also estimated. Two numerical examples are provided to illustrate the performances of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures

    Haghi, Rad; Molenaar, David P; Ashuri, Turaj; Van der Valk, Paul L C

    2014-01-01

    In the current offshore wind turbine support structure design method, the tower and foundation, which form the support structure are designed separately by the turbine and foundation designer. This method yields a suboptimal design and it results in a heavy, overdesigned and expensive support structure. This paper presents an integrated multidisciplinary approach to design the tower and foundation simultaneously. Aerodynamics, hydrodynamics, structure and soil mechanics are the modeled disciplines to capture the full dynamic behavior of the foundation and tower under different environmental conditions. The objective function to be minimized is the mass of the support structure. The model includes various design constraints: local and global buckling, modal frequencies, and fatigue damage along different stations of the structure. To show the usefulness of the method, an existing SWT-3.6-107 offshore wind turbine where its tower and foundation are designed separately is used as a case study. The result of the integrated multidisciplinary design optimization shows 12.1% reduction in the mass of the support structure, while satisfying all the design constraints

  3. Composite Differential Evolution with Modified Oracle Penalty Method for Constrained Optimization Problems

    Minggang Dong

    2014-01-01

    Full Text Available Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE for constrained optimization problems (COPs. More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems.

  4. Scheduling Appliances with GA, TLBO, FA, OSR and Their Hybrids Using Chance Constrained Optimization for Smart Homes

    Zunaira Nadeem

    2018-04-01

    Full Text Available In this paper, we design a controller for home energy management based on following meta-heuristic algorithms: teaching learning-based optimization (TLBO, genetic algorithm (GA, firefly algorithm (FA and optimal stopping rule (OSR theory. The principal goal of designing this controller is to reduce the energy consumption of residential sectors while reducing consumer’s electricity bill and maximizing user comfort. Additionally, we propose three hybrid schemes OSR-GA, OSR-TLBO and OSR-FA, by combining the best features of existing algorithms. We have also optimized the desired parameters: peak to average ratio, energy consumption, cost, and user comfort (appliance waiting time for 20, 50, 100 and 200 heterogeneous homes in two steps. In the first step, we obtain the optimal scheduling of home appliances implementing our aforementioned hybrid schemes for single and multiple homes while considering user preferences and threshold base policy. In the second step, we formulate our problem through chance constrained optimization. Simulation results show that proposed hybrid scheduling schemes outperformed for single and multiple homes and they shift the consumer load demand exceeding a predefined threshold to the hours where the electricity price is low thus following the threshold base policy. This helps to reduce electricity cost while considering the comfort of a user by minimizing delay and peak to average ratio. In addition, chance-constrained optimization is used to ensure the scheduling of appliances while considering the uncertainties of a load hence smoothing the load curtailment. The major focus is to keep the appliances power consumption within the power constraint, while keeping power consumption below a pre-defined acceptable level. Moreover, the feasible regions of appliances electricity consumption are calculated which show the relationship between cost and energy consumption and cost and waiting time.

  5. Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems

    Axelsson, Owe; Farouq, S.; Neytcheva, M.

    2017-01-01

    Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution method s * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5

  6. Mixed Integer PDE Constrained Optimization for the Control of a Wildfire Hazard

    2017-01-01

    Constrained Optimization for the Control of a Wildfire Hazard Herausgegeben von der Professor fur Angewandte Mathematik Professor Dr. rer. nat. Armin...and H.H. Tan . Finite difference methods for solving the two-dimensional advection-diffusion equation. Int. J. Numer. Meth. Fluids, 9:75-98, 1989. 6

  7. Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems

    Axelsson, Owe; Farouq, S.; Neytcheva, M.

    2017-01-01

    Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5

  8. Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization

    Zhang Xiaomeng; Wang Jing; Xing Lei

    2011-01-01

    Purpose: The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization. Methods: After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of ''metal shadows'' in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective. Results: The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images. Conclusions: Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general ''missing data'' image reconstruction problems.

  9. Volume-constrained optimization of magnetorheological and electrorheological valves and dampers

    Rosenfeld, Nicholas C.; Wereley, Norman M.

    2004-12-01

    This paper presents a case study of magnetorheological (MR) and electrorheological (ER) valve design within a constrained cylindrical volume. The primary purpose of this study is to establish general design guidelines for volume-constrained MR valves. Additionally, this study compares the performance of volume-constrained MR valves against similarly constrained ER valves. Starting from basic design guidelines for an MR valve, a method for constructing candidate volume-constrained valve geometries is presented. A magnetic FEM program is then used to evaluate the magnetic properties of the candidate valves. An optimized MR valve is chosen by evaluating non-dimensional parameters describing the candidate valves' damping performance. A derivation of the non-dimensional damping coefficient for valves with both active and passive volumes is presented to allow comparison of valves with differing proportions of active and passive volumes. The performance of the optimized MR valve is then compared to that of a geometrically similar ER valve using both analytical and numerical techniques. An analytical equation relating the damping performances of geometrically similar MR and ER valves in as a function of fluid yield stresses and relative active fluid volume, and numerical calculations are provided to calculate each valve's damping performance and to validate the analytical calculations.

  10. Timing-Constrained FPGA Placement: A Force-Directed Formulation and Its Performance Evaluation

    Srilata Raman

    1996-01-01

    Full Text Available In this paper we present a simple but efficient timing-driven placement algorithm for FPGAs. The algorithm computes forces acting on a logic block in the FPGA to determine its relative location with respect to other blocks. The forces depend on the criticality of nets shared between the two blocks. Unlike other net-based approaches, timing constraints are incorporated directly into the force equations to guide the placement. Slot assignment is then used to move the blocks into valid slot locations on the FPGA chip. The assignment algorithm also makes use of the delay information of nets so that the final placement is able to meet the timing criteria specified for the circuit. The novelty of the approach lies in the formulation of the force equations and the manner in which weights of the nets are dynamically altered to influence the placement. Experiments conducted on industrial test circuits and MCNC circuits give very promising results and indicate that the algorithm succeeds in significantly reducing the maximum delay in the circuit. In addition, routability is not adversely affected and running time is low.

  11. Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

    Reyes, Juan Carlos De los; Schö nlieb, Carola-Bibiane

    2013-01-01

    We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

  12. Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

    Reyes, Juan Carlos De los

    2013-11-01

    We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

  13. Extended Lagrangian formulation of charge-constrained tight-binding molecular dynamics.

    Cawkwell, M J; Coe, J D; Yadav, S K; Liu, X-Y; Niklasson, A M N

    2015-06-09

    The extended Lagrangian Born-Oppenheimer molecular dynamics formalism [Niklasson, Phys. Rev. Lett., 2008, 100, 123004] has been applied to a tight-binding model under the constraint of local charge neutrality to yield microcanonical trajectories with both precise, long-term energy conservation and a reduced number of self-consistent field optimizations at each time step. The extended Lagrangian molecular dynamics formalism restores time reversal symmetry in the propagation of the electronic degrees of freedom, and it enables the efficient and accurate self-consistent optimization of the chemical potential and atomwise potential energy shifts in the on-site elements of the tight-binding Hamiltonian that are required when enforcing local charge neutrality. These capabilities are illustrated with microcanonical molecular dynamics simulations of a small metallic cluster using an sd-valent tight-binding model for titanium. The effects of weak dissipation on the propagation of the auxiliary degrees of freedom for the chemical potential and on-site Hamiltonian matrix elements that is used to counteract the accumulation of numerical noise during trajectories was also investigated.

  14. Characterization of new functionalized calcium carbonate-polycaprolactone composite material for application in geometry-constrained drug release formulation development.

    Wagner-Hattler, Leonie; Schoelkopf, Joachim; Huwyler, Jörg; Puchkov, Maxim

    2017-10-01

    A new mineral-polymer composite (FCC-PCL) performance was assessed to produce complex geometries to aid in development of controlled release tablet formulations. The mechanical characteristics of a developed material such as compactibility, compressibility and elastoplastic deformation were measured. The results and comparative analysis versus other common excipients suggest efficient formation of a complex, stable and impermeable geometries for constrained drug release modifications under compression. The performance of the proposed composite material has been tested by compacting it into a geometrically altered tablet (Tablet-In-Cup, TIC) and the drug release was compared to commercially available product. The TIC device exhibited a uniform surface, showed high physical stability, and showed absence of friability. FCC-PCL composite had good binding properties and good compactibility. It was possible to reveal an enhanced plasticity characteristic of a new material which was not present in the individual components. The presented FCC-PCL composite mixture has the potential to become a successful tool to formulate controlled-release dosage solid forms.

  15. Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization

    Xiao Yunhai; Hu Qingjie

    2008-01-01

    An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection

  16. A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

    R. Venkata Rao

    2014-01-01

    Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

  17. An L∞/L1-Constrained Quadratic Optimization Problem with Applications to Neural Networks

    Leizarowitz, Arie; Rubinstein, Jacob

    2003-01-01

    Pattern formation in associative neural networks is related to a quadratic optimization problem. Biological considerations imply that the functional is constrained in the L ∞ norm and in the L 1 norm. We consider such optimization problems. We derive the Euler-Lagrange equations, and construct basic properties of the maximizers. We study in some detail the case where the kernel of the quadratic functional is finite-dimensional. In this case the optimization problem can be fully characterized by the geometry of a certain convex and compact finite-dimensional set

  18. Optimal information transfer in enzymatic networks: A field theoretic formulation

    Samanta, Himadri S.; Hinczewski, Michael; Thirumalai, D.

    2017-07-01

    Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus [Hinczewski and Thirumalai, Phys. Rev. X 4, 041017 (2014), 10.1103/PhysRevX.4.041017]. We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudointermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudointermediate. Surprisingly, in these examples the minimum error computed using simulations that take nonlinearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second-order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in

  19. Topology optimization of acoustic-structure interaction problems using a mixed finite element formulation

    Yoon, Gil Ho; Jensen, Jens Stissing; Sigmund, Ole

    2007-01-01

    given during the optimization process. In this paper we circumvent the explicit boundary representation by using a mixed finite element formulation with displacements and pressure as primary variables (a u/p-formulation). The Helmholtz equation is obtained as a special case of the mixed formulation...... for the elastic shear modulus equating to zero. Hence, by spatial variation of the mass density, shear and bulk moduli we are able to solve the coupled problem by the mixed formulation. Using this modelling approach, the topology optimization procedure is simply implemented as a standard density approach. Several...... two-dimensional acoustic-structure problems are optimized in order to verify the proposed method....

  20. A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

    Liu, Qingshan; Guo, Zhishan; Wang, Jun

    2012-02-01

    In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

  1. Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

    Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

    2018-05-01

    Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

  2. On meeting capital requirements with a chance-constrained optimization model.

    Atta Mills, Ebenezer Fiifi Emire; Yu, Bo; Gu, Lanlan

    2016-01-01

    This paper deals with a capital to risk asset ratio chance-constrained optimization model in the presence of loans, treasury bill, fixed assets and non-interest earning assets. To model the dynamics of loans, we introduce a modified CreditMetrics approach. This leads to development of a deterministic convex counterpart of capital to risk asset ratio chance constraint. We pursue the scope of analyzing our model under the worst-case scenario i.e. loan default. The theoretical model is analyzed by applying numerical procedures, in order to administer valuable insights from a financial outlook. Our results suggest that, our capital to risk asset ratio chance-constrained optimization model guarantees banks of meeting capital requirements of Basel III with a likelihood of 95 % irrespective of changes in future market value of assets.

  3. A first-order multigrid method for bound-constrained convex optimization

    Kočvara, Michal; Mohammed, S.

    2016-01-01

    Roč. 31, č. 3 (2016), s. 622-644 ISSN 1055-6788 R&D Projects: GA ČR(CZ) GAP201/12/0671 Grant - others:European Commission - EC(XE) 313781 Institutional support: RVO:67985556 Keywords : bound-constrained optimization * multigrid methods * linear complementarity problems Subject RIV: BA - General Mathematics Impact factor: 1.023, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0460326.pdf

  4. Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

    He, Longfei; Xu, Zhaoguang; Niu, Zhanwen

    2014-01-01

    We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optim...

  5. Curcumin phytosomal softgel formulation: Development, optimization and physicochemical characterization.

    Allam, Ahmed N; Komeil, Ibrahim A; Abdallah, Ossama Y

    2015-09-01

    Curcumin, a naturally occurring lipophilic molecule can exert multiple and diverse bioactivities. However, its limited aqueous solubility and extensive presystemic metabolism restrict its bioavailability. Curcumin phytosomes were prepared by a simple solvent evaporation method where free flowing powder was obtained in addition to a newly developed semisolid formulation to increase curcumin content in softgels. Phytosomal powder was characterized in terms of drug content and zeta potential. Thirteen different softgel formulations were developed using oils such as Miglyol 812, castor oil and oleic acid, a hydrophilic vehicle such as PEG 400 and bioactive surfactants such as Cremophor EL and KLS P 124. Selected formulations were characterized in terms of curcumin in vitro dissolution. TEM analysis revealed good stability and a spherical, self-closed structure of curcumin phytosomes in complex formulations. Stability studies of chosen formulations prepared using the hydrophilic vehicle revealed a stable curcumin dissolution pattern. In contrast, a dramatic decrease in curcumin dissolution was observed in case of phytosomes formulated in oily vehicles.

  6. Curcumin phytosomal softgel formulation: Development, optimization and physicochemical characterization

    Allam Ahmed N.

    2015-09-01

    Full Text Available Curcumin, a naturally occurring lipophilic molecule can exert multiple and diverse bioactivities. However, its limited aqueous solubility and extensive presystemic metabolism restrict its bioavailability. Curcumin phytosomes were prepared by a simple solvent evaporation method where free flowing powder was obtained in addition to a newly developed semisolid formulation to increase curcumin content in softgels. Phytosomal powder was characterized in terms of drug content and zeta potential. Thirteen different softgel formulations were developed using oils such as Miglyol 812, castor oil and oleic acid, a hydrophilic vehicle such as PEG 400 and bioactive surfactants such as Cremophor EL and KLS P 124. Selected formulations were characterized in terms of curcumin in vitro dissolution. TEM analysis revealed good stability and a spherical, self-closed structure of curcumin phytosomes in complex formulations. Stability studies of chosen formulations prepared using the hydrophilic vehicle revealed a stable curcumin dissolution pattern. In contrast, a dramatic decrease in curcumin dissolution was observed in case of phytosomes formulated in oily vehicles.

  7. Formulation and optimization of solid lipid nanoparticle formulation for pulmonary delivery of budesonide using Taguchi and Box-Behnken design.

    Emami, J; Mohiti, H; Hamishehkar, H; Varshosaz, J

    2015-01-01

    Budesonide is a potent non-halogenated corticosteroid with high anti-inflammatory effects. The lungs are an attractive route for non-invasive drug delivery with advantages for both systemic and local applications. The aim of the present study was to develop, characterize and optimize a solid lipid nanoparticle system to deliver budesonide to the lungs. Budesonide-loaded solid lipid nanoparticles were prepared by the emulsification-solvent diffusion method. The impact of various processing variables including surfactant type and concentration, lipid content organic and aqueous volume, and sonication time were assessed on the particle size, zeta potential, entrapment efficiency, loading percent and mean dissolution time. Taguchi design with 12 formulations along with Box-Behnken design with 17 formulations was developed. The impact of each factor upon the eventual responses was evaluated, and the optimized formulation was finally selected. The size and morphology of the prepared nanoparticles were studied using scanning electron microscope. Based on the optimization made by Design Expert 7(®) software, a formulation made of glycerol monostearate, 1.2 % polyvinyl alcohol (PVA), weight ratio of lipid/drug of 10 and sonication time of 90 s was selected. Particle size, zeta potential, entrapment efficiency, loading percent, and mean dissolution time of adopted formulation were predicted and confirmed to be 218.2 ± 6.6 nm, -26.7 ± 1.9 mV, 92.5 ± 0.52 %, 5.8 ± 0.3 %, and 10.4 ± 0.29 h, respectively. Since the preparation and evaluation of the selected formulation within the laboratory yielded acceptable results with low error percent, the modeling and optimization was justified. The optimized formulation co-spray dried with lactose (hybrid microparticles) displayed desirable fine particle fraction, mass median aerodynamic diameter (MMAD), and geometric standard deviation of 49.5%, 2.06 μm, and 2.98 μm; respectively. Our results provide fundamental data for the

  8. Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

    Salazar, Daniel; Rocco, Claudio M.; Galvan, Blas J.

    2006-01-01

    This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature

  9. Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

    Salazar, Daniel [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain) and Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: danielsalazaraponte@gmail.com; Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: crocco@reacciun.ve; Galvan, Blas J. [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain)]. E-mail: bgalvan@step.es

    2006-09-15

    This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature.

  10. CLFs-based optimization control for a class of constrained visual servoing systems.

    Song, Xiulan; Miaomiao, Fu

    2017-03-01

    In this paper, we use the control Lyapunov function (CLF) technique to present an optimized visual servo control method for constrained eye-in-hand robot visual servoing systems. With the knowledge of camera intrinsic parameters and depth of target changes, visual servo control laws (i.e. translation speed) with adjustable parameters are derived by image point features and some known CLF of the visual servoing system. The Fibonacci method is employed to online compute the optimal value of those adjustable parameters, which yields an optimized control law to satisfy constraints of the visual servoing system. The Lyapunov's theorem and the properties of CLF are used to establish stability of the constrained visual servoing system in the closed-loop with the optimized control law. One merit of the presented method is that there is no requirement of online calculating the pseudo-inverse of the image Jacobian's matrix and the homography matrix. Simulation and experimental results illustrated the effectiveness of the method proposed here. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Formulated feed preference for survival and optimal growth of ...

    Seventy-seven Bulinus snail species were fed for eight weeks with eleven diets consisting of different feed-formulations and vegetables. Snails reared exclusively on grower's mash, corn fibre meal and fish meal did not survive for up to two weeks. The result from this investigation indicatesthat there isno signiicant difference ...

  12. Optimization and Formulation of Orodispersible Tablets of Meloxicam

    ... 98.5% and fast drug release rate of 99.5% within 30 min, as compared with the conventional tablet (49.5%) . Conclusion: It is feasible to formulate orodispersible tablets of meloxican with acceptable disintegration time, rapid drug release and good hardness, which could be amenable to replication on an industrial scale.

  13. Formulation and Optimization of the Seed Extracts of Glinus lotoides ...

    A two-factor-two-level factorial was designed to investigate the combined effects on formulation variable (amount of MCC) and processing variable [compression force (CF)] on tablet properties; crushing strength (H), friability (Fr), and disintegration time (DT). From the results of multiple linear regression analysis, surface ...

  14. Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

    Wang, Yong; Cai, Zixing; Zhou, Yuren

    2009-01-01

    A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

  15. A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

    Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain

    2017-07-25

    This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

  16. Influence of cellulose derivative and ethylene glycol on optimization of lornoxicam transdermal formulation.

    Shahzad, Yasser; Khan, Qalandar; Hussain, Talib; Shah, Syed Nisar Hussain

    2013-10-01

    Lornoxicam containing topically applied lotions were formulated and optimized with the aim to deliver it transdermally. The formulated lotions were evaluated for pH, viscosity and in vitro permeation studies through silicone membrane using Franz diffusion cells. Data were fitted to linear, quadratic and cubic models and best fit model was selected to investigate the influence of variables, namely hydroxypropyl methylcellulose (HPMC) and ethylene glycol (EG) on permeation of lornoxicam from topically applied lotion formulations. The best fit quadratic model revealed that low level of HPMC and intermediate level of EG in the formulation was optimum for enhancing the drug flux across silicone membrane. FT-IR analysis confirmed absence of drug-polymer interactions. Selected optimized lotion formulation was then subjected to accelerated stability testing, sensatory perception testing and in vitro permeation across rabbit skin. The drug flux from the optimized lotion across rabbit skin was significantly better that that from the control formulation. Furthermore, sensatory perception test rated a higher acceptability while lotion was stable over stability testing period. Therefore, use of Box-Wilson statistical design successfully elaborated the influence of formulation variables on permeation of lornoxicam form topical formulations, thus, helped in optimization of the lotion formulation. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Generation and reserve dispatch in a competitive market using constrained particle swarm optimization

    Azadani, E. Nasr; Hosseinian, S.H.; Moradzadeh, B.

    2010-01-01

    Competitive bidding for energy and ancillary services is increasingly recognized as an important part of electricity markets. In addition, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on constrained particle swarm optimization (CPSO) is developed to deal with the multi-product (energy and reserve) and multi-area electricity market dispatch problem. Constraint handling is based on particle ranking and uniform distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive electricity market considering the system constraints. The proposed technique shows promising performance for smooth and non smooth cost function as well. Three different systems are examined to demonstrate the effectiveness and the accuracy of the proposed algorithm. (author)

  18. Solving Multi-Resource Constrained Project Scheduling Problem using Ant Colony Optimization

    Hsiang-Hsi Huang

    2015-01-01

    Full Text Available This paper applied Ant Colony Optimization (ACO to develop a resource constraints scheduling model to achieve the resource allocation optimization and the shortest completion time of a project under resource constraints and the activities precedence requirement for projects. Resource leveling is also discussed and has to be achieved under the resource allocation optimization in this research. Testing cases and examples adopted from the international test bank were studied for verifying the effectiveness of the proposed model. The results showed that the solutions of different cases all have a better performance within a reasonable time. These can be obtained through ACO algorithm under the same constrained conditions. A program was written for the proposed model that is able to automatically produce the project resource requirement figure after the project duration is solved.

  19. Bio-inspired varying subspace based computational framework for a class of nonlinear constrained optimal trajectory planning problems.

    Xu, Y; Li, N

    2014-09-01

    Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.

  20. Bio-inspired varying subspace based computational framework for a class of nonlinear constrained optimal trajectory planning problems

    Xu, Y; Li, N

    2014-01-01

    Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator–prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework. (paper)

  1. Constrained multi-objective optimization of radial expanders in organic Rankine cycles by firefly algorithm

    Bahadormanesh, Nikrouz; Rahat, Shayan; Yarali, Milad

    2017-01-01

    Highlights: • A multi-objective optimization for radial expander in Organic Rankine Cycles is implemented. • By using firefly algorithm, Pareto front based on the size of turbine and thermal efficiency is produced. • Tension and vibration constrains have a significant effect on optimum design points. - Abstract: Organic Rankine Cycles are viable energy conversion systems in sustainable energy systems due to their compatibility with low-temperature heat sources. In the present study, one dimensional model of radial expanders in conjunction with a thermodynamic model of organic Rankine cycles is prepared. After verification, by defining thermal efficiency of the cycle and size parameter of a radial turbine as the objective functions, a multi-objective optimization was conducted regarding tension and vibration constraints for 4 different organic working fluids (R22, R245fa, R236fa and N-Pentane). In addition to mass flow rate, evaporator temperature, maximum pressure of cycle and turbo-machinery design parameters are selected as the decision variables. Regarding Pareto fronts, by a little increase in size of radial expanders, it is feasible to reach high efficiency. Moreover, by assessing the distribution of decision variables, the variables that play a major role in trending between the objective functions are found. Effects of mechanical and vibration constrains on optimum decision variables are investigated. The results of optimization can be considered as an initial values for design of radial turbines for Organic Rankine Cycles.

  2. Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

    2014-01-01

    Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

  3. Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint.

    Bacanin, Nebojsa; Tuba, Milan

    2014-01-01

    Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

  4. A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.

    Quan, Quan; Cai, Kai-Yuan

    2016-02-01

    In equality-constrained optimization, a standard regularity assumption is often associated with feasible point methods, namely, that the gradients of constraints are linearly independent. In practice, the regularity assumption may be violated. In order to avoid such a singularity, a new projection matrix is proposed based on which a feasible point method to continuous-time, equality-constrained optimization is developed. First, the equality constraint is transformed into a continuous-time dynamical system with solutions that always satisfy the equality constraint. Second, a new projection matrix without singularity is proposed to realize the transformation. An update (or say a controller) is subsequently designed to decrease the objective function along the solutions of the transformed continuous-time dynamical system. The invariance principle is then applied to analyze the behavior of the solution. Furthermore, the proposed method is modified to address cases in which solutions do not satisfy the equality constraint. Finally, the proposed optimization approach is applied to three examples to demonstrate its effectiveness.

  5. OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD

    Dhananjay Kumar

    2016-01-01

    Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.

  6. Stability Constrained Efficiency Optimization for Droop Controlled DC-DC Conversion System

    Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

    2013-01-01

    implementing tertiary regulation. Moreover, system dynamic is affected when shifting VRs. Therefore, the stability is considered in optimization by constraining the eigenvalues arising from dynamic state space model of the system. Genetic algorithm is used in searching for global efficiency optimum while....... As the efficiency of each converter changes with output power, virtual resistances (VRs) are set as decision variables for adjusting power sharing proportion among converters. It is noteworthy that apart from restoring the voltage deviation, secondary control plays an important role to stabilize dc bus voltage when...

  7. Quality by design approach for optimizing the formulation and physical properties of extemporaneously prepared orodispersible films

    Visser, J. Caroline; Dohmen, Willem M. C.; Hinrichs, Wouter L. J.; Breitkreutz, Joerg; Frijlink, Henderik W.; Woerdenbag, Herman J.

    2015-01-01

    The quality by design (QbD) approach was applied for optimizing the formulation of extemporaneously prepared orodispersible films (ODFs) using Design-Expert Software. The starting formulation was based on earlier experiments and contained the film forming agents hypromellose and carbomer 974P and

  8. SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

    Weir, V; Zhang, J

    2015-01-01

    Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols

  9. SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

    Weir, V; Zhang, J [University of Kentucky, Lexington, KY (United States)

    2015-06-15

    Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols.

  10. Reinforcement learning solution for HJB equation arising in constrained optimal control problem.

    Luo, Biao; Wu, Huai-Ning; Huang, Tingwen; Liu, Derong

    2015-11-01

    The constrained optimal control problem depends on the solution of the complicated Hamilton-Jacobi-Bellman equation (HJBE). In this paper, a data-based off-policy reinforcement learning (RL) method is proposed, which learns the solution of the HJBE and the optimal control policy from real system data. One important feature of the off-policy RL is that its policy evaluation can be realized with data generated by other behavior policies, not necessarily the target policy, which solves the insufficient exploration problem. The convergence of the off-policy RL is proved by demonstrating its equivalence to the successive approximation approach. Its implementation procedure is based on the actor-critic neural networks structure, where the function approximation is conducted with linearly independent basis functions. Subsequently, the convergence of the implementation procedure with function approximation is also proved. Finally, its effectiveness is verified through computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

    Ono, Masahiro; Kuwata, Yoshiaki

    2013-01-01

    A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

  12. Optimal Component Lumping: problem formulation and solution techniques

    Lin, Bao; Leibovici, Claude F.; Jørgensen, Sten Bay

    2008-01-01

    This paper presents a systematic method for optimal lumping of a large number of components in order to minimize the loss of information. In principle, a rigorous composition-based model is preferable to describe a system accurately. However, computational intensity and numerical issues restrict ...

  13. Preventive Security-Constrained Optimal Power Flow Considering UPFC Control Modes

    Xi Wu

    2017-08-01

    Full Text Available The successful application of the unified power flow controller (UPFC provides a new control method for the secure and economic operation of power system. In order to make the full use of UPFC and improve the economic efficiency and static security of a power system, a preventive security-constrained power flow optimization method considering UPFC control modes is proposed in this paper. Firstly, an iterative method considering UPFC control modes is deduced for power flow calculation. Taking into account the influence of different UPFC control modes on the distribution of power flow after N-1 contingency, the optimization model is then constructed by setting a minimal system operation cost and a maximum static security margin as the objective. Based on this model, the particle swarm optimization (PSO algorithm is utilized to optimize power system operating parameters and UPFC control modes simultaneously. Finally, a standard IEEE 30-bus system is utilized to demonstrate that the proposed method fully exploits the potential of static control of UPFC and significantly increases the economic efficiency and static security of the power system.

  14. Incorporating Charging/Discharging Strategy of Electric Vehicles into Security-Constrained Optimal Power Flow to Support High Renewable Penetration

    Kyungsung An

    2017-05-01

    Full Text Available This research aims to improve the operational efficiency and security of electric power systems at high renewable penetration by exploiting the envisioned controllability or flexibility of electric vehicles (EVs; EVs interact with the grid through grid-to-vehicle (G2V and vehicle-to-grid (V2G services to ensure reliable and cost-effective grid operation. This research provides a computational framework for this decision-making process. Charging and discharging strategies of EV aggregators are incorporated into a security-constrained optimal power flow (SCOPF problem such that overall energy cost is minimized and operation within acceptable reliability criteria is ensured. Particularly, this SCOPF problem has been formulated for Jeju Island in South Korea, in order to lower carbon emissions toward a zero-carbon island by, for example, integrating large-scale renewable energy and EVs. On top of conventional constraints on the generators and line flows, a unique constraint on the system inertia constant, interpreted as the minimum synchronous generation, is considered to ensure grid security at high renewable penetration. The available energy constraint of the participating EV associated with the state-of-charge (SOC of the battery and market price-responsive behavior of the EV aggregators are also explored. Case studies for the Jeju electric power system in 2030 under various operational scenarios demonstrate the effectiveness of the proposed method and improved operational flexibility via controllable EVs.

  15. Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

    Luo, Biao; Liu, Derong; Wu, Huai-Ning

    2018-06-01

    Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

  16. Formulation, optimization and evaluation of levocetirizine dihyrochloride oral thin strip

    J Gunjan Patel

    2012-01-01

    Full Text Available The aim of present research was to develop a fast releasing oral polymeric film, with good mechanical properties, instant disintegration and dissolution, producing an acceptable taste when placed on tongue. Solvent casting method was used to prepare oral films. Levocetirizine dihydrochloride, an antihistaminic was incorporated to relieve the symptoms of allergic rhinitis. The polymers selected were HPMC E 15 and PVA. Propylene glycol was the plasticizers used. Nine batches of films with drug were prepared using different combinations of polymers and plasticizer concentration. The resultant films were evaluated for weight variation, content uniformity, folding endurance, thickness, surface pH, in vitro disintegration and in vitro dissolution. The optimized films which disintegrated in less than 30 sec, releasing 85-98% of drug within 2 minutes. The percentage release was varying with concentration of plasticizer and polymer. The films made with HPMC: PVA (1:2 released 96% of drug in 1 min, which was the best release amongst all.

  17. A Variant of the Topkis-Veinott Method for Solving Inequality Constrained Optimization Problems

    Birge, J. R.; Qi, L.; Wei, Z.

    2000-01-01

    In this paper we give a variant of the Topkis-Veinott method for solving inequality constrained optimization problems. This method uses a linearly constrained positive semidefinite quadratic problem to generate a feasible descent direction at each iteration. Under mild assumptions, the algorithm is shown to be globally convergent in the sense that every accumulation point of the sequence generated by the algorithm is a Fritz-John point of the problem. We introduce a Fritz-John (FJ) function, an FJ1 strong second-order sufficiency condition (FJ1-SSOSC), and an FJ2 strong second-order sufficiency condition (FJ2-SSOSC), and then show, without any constraint qualification (CQ), that (i) if an FJ point z satisfies the FJ1-SSOSC, then there exists a neighborhood N(z) of z such that, for any FJ point y element of N(z) {z } , f 0 (y) ≠ f 0 (z) , where f 0 is the objective function of the problem; (ii) if an FJ point z satisfies the FJ2-SSOSC, then z is a strict local minimum of the problem. The result (i) implies that the entire iteration point sequence generated by the method converges to an FJ point. We also show that if the parameters are chosen large enough, a unit step length can be accepted by the proposed algorithm

  18. Convex optimisation approach to constrained fuel optimal control of spacecraft in close relative motion

    Massioni, Paolo; Massari, Mauro

    2018-05-01

    This paper describes an interesting and powerful approach to the constrained fuel-optimal control of spacecraft in close relative motion. The proposed approach is well suited for problems under linear dynamic equations, therefore perfectly fitting to the case of spacecraft flying in close relative motion. If the solution of the optimisation is approximated as a polynomial with respect to the time variable, then the problem can be approached with a technique developed in the control engineering community, known as "Sum Of Squares" (SOS), and the constraints can be reduced to bounds on the polynomials. Such a technique allows rewriting polynomial bounding problems in the form of convex optimisation problems, at the cost of a certain amount of conservatism. The principles of the techniques are explained and some application related to spacecraft flying in close relative motion are shown.

  19. A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality

    Cheung, KW; So, HC; Ma, W.-K.; Chan, YT

    2006-12-01

    The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.

  20. Racing Sampling Based Microimmune Optimization Approach Solving Constrained Expected Value Programming

    Kai Yang

    2016-01-01

    Full Text Available This work investigates a bioinspired microimmune optimization algorithm to solve a general kind of single-objective nonlinear constrained expected value programming without any prior distribution. In the study of algorithm, two lower bound sample estimates of random variables are theoretically developed to estimate the empirical values of individuals. Two adaptive racing sampling schemes are designed to identify those competitive individuals in a given population, by which high-quality individuals can obtain large sampling size. An immune evolutionary mechanism, along with a local search approach, is constructed to evolve the current population. The comparative experiments have showed that the proposed algorithm can effectively solve higher-dimensional benchmark problems and is of potential for further applications.

  1. Optimal Financing Decisions of Two Cash-Constrained Supply Chains with Complementary Products

    Yuting Li

    2016-04-01

    Full Text Available In recent years; financing difficulties have been obsessed small and medium enterprises (SMEs; especially emerging SMEs. Inter-members’ joint financing within a supply chain is one of solutions for SMEs. How about members’ joint financing of inter-supply chains? In order to answer the question, we firstly employ the Stackelberg game to propose three kinds of financing decision models of two cash-constrained supply chains with complementary products. Secondly, we analyze qualitatively these models and find the joint financing decision of the two supply chains is the most optimal one. Lastly, we conduct some numerical simulations not only to illustrate above results but also to find that the larger are cross-price sensitivity coefficients; the higher is the motivation for participants to make joint financing decisions; and the more are profits for them to gain.

  2. Multivariate constrained shape optimization: Application to extrusion bell shape for pasta production

    Sarghini, Fabrizio; De Vivo, Angela; Marra, Francesco

    2017-10-01

    Computational science and engineering methods have allowed a major change in the way products and processes are designed, as validated virtual models - capable to simulate physical, chemical and bio changes occurring during production processes - can be realized and used in place of real prototypes and performing experiments, often time and money consuming. Among such techniques, Optimal Shape Design (OSD) (Mohammadi & Pironneau, 2004) represents an interesting approach. While most classical numerical simulations consider fixed geometrical configurations, in OSD a certain number of geometrical degrees of freedom is considered as a part of the unknowns: this implies that the geometry is not completely defined, but part of it is allowed to move dynamically in order to minimize or maximize the objective function. The applications of optimal shape design (OSD) are uncountable. For systems governed by partial differential equations, they range from structure mechanics to electromagnetism and fluid mechanics or to a combination of the three. This paper presents one of possible applications of OSD, particularly how extrusion bell shape, for past production, can be designed by applying a multivariate constrained shape optimization.

  3. Loading pattern optimization with maximum utilization of discharging fuel employing adaptively constrained discontinuous penalty function

    Park, T. K.; Joo, H. G.; Kim, C. H.

    2010-01-01

    In order to find the most economical loading pattern (LP) considering multi-cycle fuel loading, multi-objective fuel LP optimization problems are examined by employing an adaptively constrained discontinuous penalty function (ACDPF) method. This is an improved method to simplify the complicated acceptance logic of the original DPF method in that the stochastic effects caused by the different random number sequence can be reduced. The effectiveness of the multi-objective simulated annealing (SA) algorithm employing ACDPF is examined for the reload core LP of Cycle 4 of Yonggwang Nuclear Unit 4. Several optimization runs are performed with different numbers of objectives consisting of cycle length and average burnup of fuels to be discharged or reloaded. The candidate LPs obtained from the multi-objective optimization runs turn out to be better than the reference LP in the aspects of cycle length and utilization of given fuels. It is note that the proposed ACDPF based MOSA algorithm can be a practical method to obtain an economical LP considering multi-cycle fuel loading. (authors)

  4. Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

    Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

    2013-10-01

    This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example.

  5. Thermodynamic optimization of mixed refrigerant Joule- Thomson systems constrained by heat transfer considerations

    Hinze, J F; Klein, S A; Nellis, G F

    2015-01-01

    Mixed refrigerant (MR) working fluids can significantly increase the cooling capacity of a Joule-Thomson (JT) cycle. The optimization of MRJT systems has been the subject of substantial research. However, most optimization techniques do not model the recuperator in sufficient detail. For example, the recuperator is usually assumed to have a heat transfer coefficient that does not vary with the mixture. Ongoing work at the University of Wisconsin-Madison has shown that the heat transfer coefficients for two-phase flow are approximately three times greater than for a single phase mixture when the mixture quality is between 15% and 85%. As a result, a system that optimizes a MR without also requiring that the flow be in this quality range may require an extremely large recuperator or not achieve the performance predicted by the model. To ensure optimal performance of the JT cycle, the MR should be selected such that it is entirely two-phase within the recuperator. To determine the optimal MR composition, a parametric study was conducted assuming a thermodynamically ideal cycle. The results of the parametric study are graphically presented on a contour plot in the parameter space consisting of the extremes of the qualities that exist within the recuperator. The contours show constant values of the normalized refrigeration power. This ‘map’ shows the effect of MR composition on the cycle performance and it can be used to select the MR that provides a high cooling load while also constraining the recuperator to be two phase. The predicted best MR composition can be used as a starting point for experimentally determining the best MR. (paper)

  6. Prolonged release matrix tablet of pyridostigmine bromide: formulation and optimization using statistical methods.

    Bolourchian, Noushin; Rangchian, Maryam; Foroutan, Seyed Mohsen

    2012-07-01

    The aim of this study was to design and optimize a prolonged release matrix formulation of pyridostigmine bromide, an effective drug in myasthenia gravis and poisoning with nerve gas, using hydrophilic - hydrophobic polymers via D-optimal experimental design. HPMC and carnauba wax as retarding agents as well as tricalcium phosphate were used in matrix formulation and considered as independent variables. Tablets were prepared by wet granulation technique and the percentage of drug released at 1 (Y(1)), 4 (Y(2)) and 8 (Y(3)) hours were considered as dependent variables (responses) in this investigation. These experimental responses were best fitted for the cubic, cubic and linear models, respectively. The optimal formulation obtained in this study, consisted of 12.8 % HPMC, 24.4 % carnauba wax and 26.7 % tricalcium phosphate, had a suitable prolonged release behavior followed by Higuchi model in which observed and predicted values were very close. The study revealed that D-optimal design could facilitate the optimization of prolonged release matrix tablet containing pyridostigmine bromide. Accelerated stability studies confirmed that the optimized formulation remains unchanged after exposing in stability conditions for six months.

  7. A policy iteration approach to online optimal control of continuous-time constrained-input systems.

    Modares, Hamidreza; Naghibi Sistani, Mohammad-Bagher; Lewis, Frank L

    2013-09-01

    This paper is an effort towards developing an online learning algorithm to find the optimal control solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on the policy iteration (PI) technique which has recently evolved as a major technique for solving optimal control problems. Although a number of online PI algorithms have been developed for CT systems, none of them take into account the input constraints caused by actuator saturation. In practice, however, ignoring these constraints leads to performance degradation or even system instability. In this paper, to deal with the input constraints, a suitable nonquadratic functional is employed to encode the constraints into the optimization formulation. Then, the proposed PI algorithm is implemented on an actor-critic structure to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with this nonquadratic cost functional in an online fashion. That is, two coupled neural network (NN) approximators, namely an actor and a critic are tuned online and simultaneously for approximating the associated HJB solution and computing the optimal control policy. The critic is used to evaluate the cost associated with the current policy, while the actor is used to find an improved policy based on information provided by the critic. Convergence to a close approximation of the HJB solution as well as stability of the proposed feedback control law are shown. Simulation results of the proposed method on a nonlinear CT system illustrate the effectiveness of the proposed approach. Copyright © 2013 ISA. All rights reserved.

  8. Optimization Formulations for the Maximum Nonlinear Buckling Load of Composite Structures

    Lindgaard, Esben; Lund, Erik

    2011-01-01

    This paper focuses on criterion functions for gradient based optimization of the buckling load of laminated composite structures considering different types of buckling behaviour. A local criterion is developed, and is, together with a range of local and global criterion functions from literature......, benchmarked on a number of numerical examples of laminated composite structures for the maximization of the buckling load considering fiber angle design variables. The optimization formulations are based on either linear or geometrically nonlinear analysis and formulated as mathematical programming problems...... solved using gradient based techniques. The developed local criterion is formulated such it captures nonlinear effects upon loading and proves useful for both analysis purposes and as a criterion for use in nonlinear buckling optimization. © 2010 Springer-Verlag....

  9. A New Optimization Strategy to Improve Design of Hydrogen Network Based Formulation of Hydrogen Consumers

    M. R. S. Birjandi

    2018-03-01

    Full Text Available This paper describes a shortcut model for formulating hydrogen consumers in hydrogen network based on inlet/outlet flow rate and inlet/outlet hydrogen purity. The formulation procedure is obtained using nonlinear regression of industrial data and represents the relationship between the flow rate and purity of outlet and inlet streams. The proposed model can estimate outlet flow rate and purity of hydrogen by changing inlet flow rate and purity of hydrogen. The shortcut model is used to achieve optimal operation of consumers and it optimizes hydrogen network design.

  10. Exploring the impact of constraints in quantum optimal control through a kinematic formulation

    Donovan, Ashley; Beltrani, Vincent; Rabitz, Herschel

    2013-01-01

    Highlights: • This work lays a foundation for studying constraints in quantum control simulations. • The underlying quantum control landscape in the presence of constraints is explored. • Constrained controls can encounter suboptimal traps in the landscape. • The controls are kinematic stand-ins for dynamic time-dependent controls. • A method is developed to transfer between constrained kinematic and dynamic controls. - Abstract: The control of quantum dynamics with tailored laser fields is finding growing experimental success. In practice, experiments will be subject to constraints on the controls that may prevent full optimization of the objective. A framework is presented for systematically investigating the impact of constraints in quantum optimal control simulations using a two-stage process starting with simple time-independent kinematic controls, which act as stand-ins for the traditional dynamic controls. The objective is a state-to-state transition probability, and constraints are introduced by restricting the kinematic control variables during optimization. As a second stage, the means to map from kinematic to dynamic controls is presented, thus enabling a simplified overall procedure for exploring how limited resources affect the ability to optimize the objective. A demonstration of the impact of imposing several types of kinematic constraints is investigated, thereby offering insight into constrained quantum controls

  11. Mini-batch optimized full waveform inversion with geological constrained gradient filtering

    Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai

    2018-05-01

    High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.

  12. Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

    Liu, Qiang; Chattopadhyay, Aditi

    2000-06-01

    Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

  13. Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

    Longfei He

    2014-01-01

    Full Text Available We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optimization algorithm to obtain joint optimal production quantities combination for maximizing overall profit under regulatory policies, respectively. Furthermore, numerical studies by featuring exponentially distributed demand compare systemwide performances in various scenarios. We build the “carbon emission elasticity of profit (CEEP” index as a metric to evaluate the impact of regulatory policies on both chainwide emissions and profit. Our results manifest that by facilitating the mandatory emission cap in proper installation within the network one can balance well effective emission reduction and associated acceptable profit loss. The outcome that CEEP index when implementing Carbon emission tax is elastic implies that the scale of profit loss is greater than that of emission reduction, which shows that this policy is less effective than mandatory cap from industry standpoint at least.

  14. Global optimization for overall HVAC systems - Part I problem formulation and analysis

    Lu Lu; Cai Wenjian; Chai, Y.S.; Xie Lihua

    2005-01-01

    This paper presents the global optimization technologies for overall heating, ventilating and air conditioning (HVAC) systems. The objective function of global optimization and constraints are formulated based on mathematical models of the major components. All these models are associated with power consumption components and heat exchangers for transferring cooling load. The characteristics of all the major components are briefly introduced by models, and the interactions between them are analyzed and discussed to show the complications of the problem. According to the characteristics of the operating components, the complicated original optimization problem for overall HVAC systems is transformed and simplified into a compact form ready for optimization

  15. Preparation of finasteride capsules-loaded drug nanoparticles: formulation, optimization, in vitro, and pharmacokinetic evaluation

    Ahmed TA

    2016-02-01

    Full Text Available Tarek A Ahmed1,2 1Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia; 2Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Al-Azhar University, Cairo, Egypt Abstract: In this study, optimized freeze-dried finasteride nanoparticles (NPs were prepared from drug nanosuspension formulation that was developed using the bottom–up technique. The effects of four formulation and processing variables that affect the particle size and solubility enhancement of the NPs were explored using the response surface optimization design. The optimized formulation was morphologically characterized using transmission electron microscopy (TEM. Physicochemical interaction among the studied components was investigated. Crystalline change was investigated using X-ray powder diffraction (XRPD. Crystal growth of the freeze-dried NPs was compared to the corresponding aqueous drug nanosuspension. Freeze-dried NPs formulation was subsequently loaded into hard gelatin capsules that were examined for in vitro dissolution and pharmacokinetic behavior. Results revealed that in most of the studied variables, some of the quadratic and interaction effects had a significant effect on the studied responses. TEM image illustrated homogeneity and shape of the prepared NPs. No interaction among components was noticed. XRPD confirmed crystalline state change in the optimized NPs. An enhancement in the dissolution rate of more than 2.5 times from capsules filled with optimum drug NPs, when compared to capsules filled with pure drug, was obtained. Crystal growth, due to Ostwald ripening phenomenon and positive Gibbs free energy, was reduced following lyophilization of the nanosuspension formulation. Pharmacokinetic parameters from drug NPs were superior to that of pure drug and drug microparticles. In conclusion, freeze-dried NPs based on drug nanosuspension formulation is a successful

  16. Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

    Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

    2012-12-01

    Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

  17. Improved Formulation for the Optimization of Wind Turbine Placement in a Wind Farm

    Zong Woo Geem

    2013-01-01

    Full Text Available As an alternative to fossil fuels, wind can be considered because it is a renewable and greenhouse gas-free natural resource. When wind power is generated by wind turbines in a wind farm, the optimal placement of turbines is critical because different layouts produce different efficiencies. The objective of the wind turbine placement problem is to maximize the generated power while minimizing the cost in installing the turbines. This study proposes an efficient optimization formulation for the optimal layout of wind turbine placements under the resources (e.g., number of turbines or budget limit by introducing corresponding constraints. The proposed formulation gave users more conveniences in considering resources and budget bounds. After performing the optimization, results were compared using two different methods (branch and bound method and genetic algorithm and two different objective functions.

  18. Accelerated Optimization in the PDE Framework: Formulations for the Active Contour Case

    Yezzi, Anthony; Sundaramoorthi, Ganesh

    2017-01-01

    Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE's. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

  19. Accelerated Optimization in the PDE Framework: Formulations for the Active Contour Case

    Yezzi, Anthony

    2017-11-27

    Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE\\'s. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

  20. Systematic evaluation of common lubricants for optimal use in tablet formulation.

    Paul, Shubhajit; Sun, Changquan Calvin

    2018-05-30

    As an essential formulation component for large-scale tablet manufacturing, the lubricant preserves tooling by reducing die-wall friction. Unfortunately, lubrication also often results in adverse effects on tablet characteristics, such as prolonged disintegration, slowed dissolution, and reduced mechanical strength. Therefore, the choice of lubricant and its optimal concentration in a tablet formulation is a critical decision in tablet formulation development to attain low die-wall friction while minimizing negative impact on other tablet properties. Three commercially available tablet lubricants, i.e., magnesium stearate, sodium stearyl fumerate, and stearic acid, were systematically investigated in both plastic and brittle matrices to elucidate their effects on reducing die-wall friction, tablet strength, tablet hardness, tablet friability, and tablet disintegration kinetics. Clear understanding of the lubrication efficiency of commonly used lubricants as well as their impact on tablet characteristics would help future tablet formulation efforts. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Optimization of carboxylate-terminated poly(amidoamine) dendrimer-mediated cisplatin formulation.

    Kulhari, Hitesh; Pooja, Deep; Singh, Mayank K; Chauhan, Abhay S

    2015-02-01

    Abstract Cisplatin is mainly used in the treatment of ovarian, head and neck and testicular cancer. Poor solubility and non-specific interactions causes hurdles in the development of successful cisplatin formulation. There were few reports on poly(amidoamine) (PAMAM) dendrimer-cisplatin complexes for anticancer treatment. But the earlier research was mainly focused on therapeutic effect of PAMAM dendrimer-cisplatin complex, with less attention paid on the formulation development of these complexes. Objective of the present study is to optimize and validate the carboxylate-terminated, EDA core PAMAM dendrimer-based cisplatin formulation with respect to various variables such as dendrimer core, generation, drug entrapment, purification, yield, reproducibility, stability, storage and in-vitro release. Dendrimer-cisplatin complex was prepared by an efficient method which significantly increases the % platinum (Pt) content along with the product yield. Dendrimers showed reproducible (∼27%) platinum loading by weight. Variation in core and generations does not produce significant change in the % Pt content. Percentage Pt content of dendrimeric formulation increases with increase in drug/dendrimer mole ratio. Formulation with low drug/dendrimer mole ratio showed delayed release compared to the higher drug/dendrimer mole ratio; these dendrimer formulations are stable in room temperature. In vitro release profiles of the stored dendrimer-cisplatin samples showed comparatively slow release of cisplatin, which may be due to formation of strong bond between cisplatin and dendrimer. This study will contribute to create a fine print for the formulation development of PAMAM dendrimer-cisplatin complexes.

  2. Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

    Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

    2003-08-01

    For two decades now, the use of Remote Sensing/Precision Agriculture to improve farm yields while reducing the use of polluting chemicals and the limited water supply has been a major goal. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, farm efficiency must increase to meet future food requirements and to make farming a sustainable, profitable occupation. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The real goal is to increase farm profitability by identifying the additional treatments of chemicals and water that increase revenues more than they increase costs and do no exceed pollution standards (constrained optimization). Even though the economic and environmental benefits appear to be great, Remote Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now in place, but other needed factors have been missing. Commercial satellite systems can now image the Earth (multi-spectrally) with a resolution as fine as 2.5 m. Precision variable dispensing systems using GPS are now available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been developed. Personal computers and internet access are now in place in most farm homes and can provide a mechanism for periodically disseminating advice on what quantities of water and chemicals are needed in specific regions of each field. Several processes have been selected that fuse the disparate sources of information on the current and historic states of the crop and soil, and the remaining resource levels available, with the critical decisions that farmers are required to make. These are done in a way that is easy for the farmer to understand and profitable to implement. A "Constrained

  3. Applications of an alternative formulation for one-layer real time optimization

    Schiavon Júnior A.L.

    2000-01-01

    Full Text Available This paper presents two applications of an alternative formulation for one-layer real time structure for control and optimization. This new formulation have arisen from predictive controller QDMC (Quadratic Dynamic Matrix Control, a type of predictive control (Model Predictive Control - MPC. At each sampling time, the values of the outputs of process are fed into the optimization-control structure which supplies the new values of the manipulated variables already considering the best conditions of process. The variables of optimization are both set-point changes and control actions. The future stationary outputs and the future stationary control actions have both a different formulation of conventional one-layer structure and they are calculated from the inverse gain matrix of the process. This alternative formulation generates a convex problem, which can be solved by less sophisticated optimization algorithms. Linear and nonlinear economic objective functions were considered. The proposed approach was applied to two linear models, one SISO (single-input/single output and the other MIMO (multiple-input/multiple-output. The results showed an excellent performance.

  4. An optimized formulation for Deprit-type Lie transformations of Taylor maps for symplectic systems

    Shi, Jicong

    1993-01-01

    An optimized iterative formulation is presented for directly transforming a Taylor map of a symplectic system into a Deprit-type Lie transformation, which is a composition of a linear transfer matrix and a single Lie transformation, to an arbitrary order

  5. [Optimization of Formulation and Process of Paclitaxel PEGylated Liposomes by Box-Behnken Response Surface Methodology].

    Shi, Ya-jun; Zhang, Xiao-feil; Guo, Qiu-ting

    2015-12-01

    To develop a procedure for preparing paclitaxel encapsulated PEGylated liposomes. The membrane hydration followed extraction method was used to prepare PEGylated liposomes. The process and formulation variables were optimized by "Box-Behnken Design (BBD)" of response surface methodology (RSM) with the amount of Soya phosphotidylcholine (SPC) and PEG2000-DSPE as well as the rate of SPC to drug as independent variables and entrapment efficiency as dependent variables for optimization of formulation variables while temperature, pressure and cycle times as independent variables and particle size and polydispersion index as dependent variables for process variables. The optimized liposomal formulation was characterized for particle size, Zeta potential, morphology and in vitro drug release. For entrapment efficiency, particle size, polydispersion index, Zeta potential, and in vitro drug release of PEGylated liposomes was found to be 80.3%, (97.15 ± 14.9) nm, 0.117 ± 0.019, (-30.3 ± 3.7) mV, and 37.4% in 24 h, respectively. The liposomes were found to be small, unilamellar and spherical with smooth surface as seen in transmission electron microscopy. The Box-Behnken response surface methodology facilitates the formulation and optimization of paclitaxel PEGylated liposomes.

  6. Cohesive phase-field fracture and a PDE constrained optimization approach to fracture inverse problems

    Tupek, Michael R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-06-30

    In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- put parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.

  7. On the optimal identification of tag sets in time-constrained RFID configurations.

    Vales-Alonso, Javier; Bueno-Delgado, María Victoria; Egea-López, Esteban; Alcaraz, Juan José; Pérez-Mañogil, Juan Manuel

    2011-01-01

    In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags.

  8. SmartFix: Indoor Locating Optimization Algorithm for Energy-Constrained Wearable Devices

    Xiaoliang Wang

    2017-01-01

    Full Text Available Indoor localization technology based on Wi-Fi has long been a hot research topic in the past decade. Despite numerous solutions, new challenges have arisen along with the trend of smart home and wearable computing. For example, power efficiency needs to be significantly improved for resource-constrained wearable devices, such as smart watch and wristband. For a Wi-Fi-based locating system, most of the energy consumption can be attributed to real-time radio scan; however, simply reducing radio data collection will cause a serious loss of locating accuracy because of unstable Wi-Fi signals. In this paper, we present SmartFix, an optimization algorithm for indoor locating based on Wi-Fi RSS. SmartFix utilizes user motion features, extracts characteristic value from history trajectory, and corrects deviation caused by unstable Wi-Fi signals. We implemented a prototype of SmartFix both on Moto 360 2nd-generation Smartwatch and on HTC One Smartphone. We conducted experiments both in a large open area and in an office hall. Experiment results demonstrate that average locating error is less than 2 meters for more than 80% cases, and energy consumption is only 30% of Wi-Fi fingerprinting method under the same experiment circumstances.

  9. Mixture experiment methods in the development and optimization of microemulsion formulations.

    Furlanetto, S; Cirri, M; Piepel, G; Mennini, N; Mura, P

    2011-06-25

    Microemulsion formulations represent an interesting delivery vehicle for lipophilic drugs, allowing for improving their solubility and dissolution properties. This work developed effective microemulsion formulations using glyburide (a very poorly-water-soluble hypoglycaemic agent) as a model drug. First, the area of stable microemulsion (ME) formations was identified using a new approach based on mixture experiment methods. A 13-run mixture design was carried out in an experimental region defined by constraints on three components: aqueous, oil and surfactant/cosurfactant. The transmittance percentage (at 550 nm) of ME formulations (indicative of their transparency and thus of their stability) was chosen as the response variable. The results obtained using the mixture experiment approach corresponded well with those obtained using the traditional approach based on pseudo-ternary phase diagrams. However, the mixture experiment approach required far less experimental effort than the traditional approach. A subsequent 13-run mixture experiment, in the region of stable MEs, was then performed to identify the optimal formulation (i.e., having the best glyburide dissolution properties). Percent drug dissolved and dissolution efficiency were selected as the responses to be maximized. The ME formulation optimized via the mixture experiment approach consisted of 78% surfactant/cosurfacant (a mixture of Tween 20 and Transcutol, 1:1, v/v), 5% oil (Labrafac Hydro) and 17% aqueous phase (water). The stable region of MEs was identified using mixture experiment methods for the first time. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. A new experimental design method to optimize formulations focusing on a lubricant for hydrophilic matrix tablets.

    Choi, Du Hyung; Shin, Sangmun; Khoa Viet Truong, Nguyen; Jeong, Seong Hoon

    2012-09-01

    A robust experimental design method was developed with the well-established response surface methodology and time series modeling to facilitate the formulation development process with magnesium stearate incorporated into hydrophilic matrix tablets. Two directional analyses and a time-oriented model were utilized to optimize the experimental responses. Evaluations of tablet gelation and drug release were conducted with two factors x₁ and x₂: one was a formulation factor (the amount of magnesium stearate) and the other was a processing factor (mixing time), respectively. Moreover, different batch sizes (100 and 500 tablet batches) were also evaluated to investigate an effect of batch size. The selected input control factors were arranged in a mixture simplex lattice design with 13 experimental runs. The obtained optimal settings of magnesium stearate for gelation were 0.46 g, 2.76 min (mixing time) for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The optimal settings for drug release were 0.33 g, 7.99 min for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The exact ratio and mixing time of magnesium stearate could be formulated according to the resulting hydrophilic matrix tablet properties. The newly designed experimental method provided very useful information for characterizing significant factors and hence to obtain optimum formulations allowing for a systematic and reliable experimental design method.

  11. Strong diffusion formulation of Markov chain ensembles and its optimal weaker reductions

    Güler, Marifi

    2017-10-01

    Two self-contained diffusion formulations, in the form of coupled stochastic differential equations, are developed for the temporal evolution of state densities over an ensemble of Markov chains evolving independently under a common transition rate matrix. Our first formulation derives from Kurtz's strong approximation theorem of density-dependent Markov jump processes [Stoch. Process. Their Appl. 6, 223 (1978), 10.1016/0304-4149(78)90020-0] and, therefore, strongly converges with an error bound of the order of lnN /N for ensemble size N . The second formulation eliminates some fluctuation variables, and correspondingly some noise terms, within the governing equations of the strong formulation, with the objective of achieving a simpler analytic formulation and a faster computation algorithm when the transition rates are constant or slowly varying. There, the reduction of the structural complexity is optimal in the sense that the elimination of any given set of variables takes place with the lowest attainable increase in the error bound. The resultant formulations are supported by numerical simulations.

  12. Multi-Objective Differential Evolution for Voltage Security Constrained Optimal Power Flow in Deregulated Power Systems

    Roselyn, J. Preetha; Devaraj, D.; Dash, Subhransu Sekhar

    2013-11-01

    Voltage stability is an important issue in the planning and operation of deregulated power systems. The voltage stability problems is a most challenging one for the system operators in deregulated power systems because of the intense use of transmission line capabilities and poor regulation in market environment. This article addresses the congestion management problem avoiding offline transmission capacity limits related to voltage stability by considering Voltage Security Constrained Optimal Power Flow (VSCOPF) problem in deregulated environment. This article presents the application of Multi Objective Differential Evolution (MODE) algorithm to solve the VSCOPF problem in new competitive power systems. The maximum of L-index of the load buses is taken as the indicator of voltage stability and is incorporated in the Optimal Power Flow (OPF) problem. The proposed method in hybrid power market which also gives solutions to voltage stability problems by considering the generation rescheduling cost and load shedding cost which relieves the congestion problem in deregulated environment. The buses for load shedding are selected based on the minimum eigen value of Jacobian with respect to the load shed. In the proposed approach, real power settings of generators in base case and contingency cases, generator bus voltage magnitudes, real and reactive power demands of selected load buses using sensitivity analysis are taken as the control variables and are represented as the combination of floating point numbers and integers. DE/randSF/1/bin strategy scheme of differential evolution with self-tuned parameter which employs binomial crossover and difference vector based mutation is used for the VSCOPF problem. A fuzzy based mechanism is employed to get the best compromise solution from the pareto front to aid the decision maker. The proposed VSCOPF planning model is implemented on IEEE 30-bus system, IEEE 57 bus practical system and IEEE 118 bus system. The pareto optimal

  13. Transungual Gel of Terbinafine Hydrochloride for the Management of Onychomycosis: Formulation, Optimization, and Evaluation.

    Thatai, Purva; Sapra, Bharti

    2017-08-01

    The present study was aimed to optimize, develop, and evaluate microemulsion and microemulsion-based gel as a vehicle for transungual drug delivery of terbinafine hydrochloride for the treatment of onychomycosis. D-optimal mixture experimental design was adopted to optimize the composition of microemulsion having amount of oil (X 1 ), Smix (mixture of surfactant and cosurfactant; X 2 ), and water (X 3 ) as the independent variables. The formulations were assessed for permeation (micrograms per square centimeter per hour; Y 1 ), particle size (nanometer; Y 2 ), and solubility of the drug in the formulation (milligrams per milliliter; Y 3 ). The microemulsion containing 3.05% oil, 24.98% Smix, and 71.96% water was selected as the optimized formulation. The microemulsion-based gel showed better penetration (∼5 folds) as well as more retention (∼9 fold) in the animal hoof as compared to the commercial cream. The techniques used to screen penetration enhancers (hydration enhancement factor, ATR-FTIR, SEM, and DSC) revealed the synergistic effect of combination of urea and n-acetyl cysteine in disruption of the structure of hoof and hence, leading to enhanced penetration of drug.

  14. Design and optimization of self-nanoemulsifying formulations for lipophilic drugs

    Zhao, Tianjing; Maniglio, Devid; Motta, Antonella; Migliaresi, Claudio; Chen, Jie; Chen, Bin

    2015-01-01

    The purpose of the current study was to develop and optimize novel self-nanoemulsifying drug delivery systems (SNEDDS) with a high proportion of essential oil as carriers for lipophilic drugs. Solubility and droplet size as a function of the composition were investigated, and a ternary phase diagram was constructed in order to identify the self-emulsification regions. The optimized SNEDDS formulation consisted of lemon essential oil (oil), Cremophor RH40 (surfactant) and Transcutol HP (co-surfactant) in the ratio 50:30:20 (v/v). Ibuprofen was chosen as the model drug. The droplet size, ζ-potential and stability of the drug-loaded optimized formulations were determined. The stability of SNEDDS was proved after triple freezing/thawing cycles and storage at 4 °C and 25 °C for 3 months. In vitro drug release studies of optimized SNEDDS revealed a significant increase of the drug release and release rate in comparison to the Ibuprofen suspension (80% versus approximately 40% in 2 h). The results indicated that these SNEDDS formulations could be used to improve the bioavailability of lipophilic drugs. (paper)

  15. A simple boundary element formulation for shape optimization of 2D continuous structures

    Luciano Mendes Bezerra; Jarbas de Carvalho Santos Junior; Arlindo Pires Lopes; Andre Luiz; Souza, A.C.

    2005-01-01

    For the design of nuclear equipment like pressure vessels, steam generators, and pipelines, among others, it is very important to optimize the shape of the structural systems to withstand prescribed loads such as internal pressures and prescribed or limiting referential values such as stress or strain. In the literature, shape optimization of frame structural systems is commonly found but the same is not true for continuous structural systems. In this work, the Boundary Element Method (BEM) is applied to simple problems of shape optimization of 2D continuous structural systems. The proposed formulation is based on the BEM and on deterministic optimization methods of zero and first order such as Powell's, Conjugate Gradient, and BFGS methods. Optimal characterization for the geometric configuration of 2D structure is obtained with the minimization of an objective function. Such function is written in terms of referential values (such as loads, stresses, strains or deformations) prescribed at few points inside or at the boundary of the structure. The use of the BEM for shape optimization of continuous structures is attractive compared to other methods that discretized the whole continuous. Several numerical examples of the application of the proposed formulation to simple engineering problems are presented. (authors)

  16. A Mathematical Formulation of the SCOLE Control Problem. Part 2: Optimal Compensator Design

    Balakrishnan, A. V.

    1988-01-01

    The study initiated in Part 1 of this report is concluded and optimal feedback control (compensator) design for stability augmentation is considered, following the mathematical formulation developed in Part 1. Co-located (rate) sensors and (force and moment) actuators are assumed, and allowing for both sensor and actuator noise, stabilization is formulated as a stochastic regulator problem. Specializing the general theory developed by the author, a complete, closed form solution (believed to be new with this report) is obtained, taking advantage of the fact that the inherent structural damping is light. In particular, it is possible to solve in closed form the associated infinite-dimensional steady-state Riccati equations. The SCOLE model involves associated partial differential equations in a single space variable, but the compensator design theory developed is far more general since it is given in the abstract wave equation formulation. The results thus hold for any multibody system so long as the basic model is linear.

  17. Quality by design approach for optimizing the formulation and physical properties of extemporaneously prepared orodispersible films.

    Visser, J Carolina; Dohmen, Willem M C; Hinrichs, Wouter L J; Breitkreutz, Jörg; Frijlink, Henderik W; Woerdenbag, Herman J

    2015-05-15

    The quality by design (QbD) approach was applied for optimizing the formulation of extemporaneously prepared orodispersible films (ODFs) using Design-Expert® Software. The starting formulation was based on earlier experiments and contained the film forming agents hypromellose and carbomer 974P and the plasticizer glycerol (Visser et al., 2015). Trometamol and disodium EDTA were added to stabilize the solution. To optimize this formulation a quality target product profile was established in which critical quality attributes (CQAs) such as mechanical properties and disintegration time were defined and quantified. As critical process parameters (CPP) that were evaluated for their effect on the CQAs the percentage of hypromellose and the percentage of glycerol as well as the drying time were chosen. Response surface methodology (RMS) was used to evaluate the effects of the CPPs on the CQAs of the final product. The main factor affecting tensile strength and Young's modulus was the percentage of glycerol. Elongation at break was mainly influenced by the drying temperature. Disintegration time was found to be sensitive to the percentage of hypromellose. From the results a design space could be created. As long as the formulation and process variables remain within this design space, a product is obtained with desired characteristics and that meets all set quality requirements. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Formulation, optimization, and evaluation of self-emulsifying drug delivery systems of nevirapine.

    Chintalapudi, Ramprasad; Murthy, T E G K; Lakshmi, K Rajya; Manohar, G Ganesh

    2015-01-01

    The aim of the present study was to formulate and optimize the self-emulsifying drug delivery systems (SEDDS) of nevirapine (NVP) by use of 2(2) factorial designs to enhance the oral absorption of NVP by improving its solubility, dissolution rate, and diffusion profile. SEDDS are the isotropic mixtures of oil, surfactant, co-surfactant and drug that form oil in water microemulsion when introduced into the aqueous phase under gentle agitation. Solubility of NVP in different oils, surfactants, and co-surfactants was determined for the screening of excipients. Pseudo-ternary phase diagrams were constructed by the aqueous titration method, and formulations were developed based on the optimum excipient combinations with the help of data obtained through the maximum micro emulsion region containing combinations of oil, surfactant, and co-surfactant. The formulations of SEDDS were optimized by 2(2) factorial designs. The optimum formulation of SEDDS contains 32.5% oleic acid, 44.16% tween 20, and 11.9% polyethylene glycol 600 as oil, surfactant, and co-surfactant respectively. The SEDDS was evaluated for the following drug content, self-emulsification time, rheological properties, zeta potential, in vitro diffusion studies, thermodynamic stability studies, and in vitro dissolution studies. An increase in dissolution was achieved by SEDDS compared to pure form of NVP. Overall, this study suggests that the dissolution and oral bioavailability of NVP could be improved by SEDDS technology.

  19. Optimization of a Functional Cookie Formulation by Using Response Surface Methodology

    Lee, L.Y.; Tan, K.S.; Liew, S.L.

    2011-01-01

    A functional cookie formulation containing oligo fructose, dietary fibre and lower calorie, fat and sugar contents than conventional cookies was optimized using Response Surface Methodology (RSM). Instant N-Oil II was used as a fat replacer, while Raftilose P95 was used as a sugar substitute with the addition of fructose to enhance sweetness. Selection of the optimal formulation was based on caloric content. An optimized formulation, V1, was obtained from the model Y = 4927.70 - 152.34X 1 - 155.42X 3 + 104.20X 3 2 + 151.71X 3 3 - 95.08X 3 4 , where Instant N-Oil II replaced 30 % of butter and 24.4 %, w/w (30.5 g) fructose replaced 40.0 %, w/w (50.0 g) sucrose. Two additional optimized formulations, S1 and S2, were proposed which contained the same ingredients as V1, but both contained 19.0 %, w/w (23.8 g) Raftilose P95. Also, S2 had a higher fat replacement level (42 %). A reference cookie prepared from a conventional recipe received significantly higher scores (P < 0.05) than the functional cookies V1, S1 and S2 in the sensory evaluation. However, when health benefits of the functional cookies were explained to the panel after the sensory evaluation had concluded, majority of the panelists stated that they would prefer S1, had they known of its health benefits. S1 contained 19.04 % fat, 8.62 % fructose and 0.74 % sucrose, namely, significantly lower fat and sucrose levels and higher fructose content than the conventional cookie. (author)

  20. JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

    Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

    2017-01-25

    Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open

  1. Optimal power flow: a bibliographic survey I. Formulations and deterministic methods

    Frank, Stephen [Colorado School of Mines, Department of Electrical Engineering and Computer Science, Golden, CO (United States); Steponavice, Ingrida [University of Jyvaskyla, Department of Mathematical Information Technology, Agora (Finland); Rebennack, Steffen [Colorado School of Mines, Division of Economics and Business, Golden, CO (United States)

    2012-09-15

    Over the past half-century, optimal power flow (OPF) has become one of the most important and widely studied nonlinear optimization problems. In general, OPF seeks to optimize the operation of electric power generation, transmission, and distribution networks subject to system constraints and control limits. Within this framework, however, there is an extremely wide variety of OPF formulations and solution methods. Moreover, the nature of OPF continues to evolve due to modern electricity markets and renewable resource integration. In this two-part survey, we survey both the classical and recent OPF literature in order to provide a sound context for the state of the art in OPF formulation and solution methods. The survey contributes a comprehensive discussion of specific optimization techniques that have been applied to OPF, with an emphasis on the advantages, disadvantages, and computational characteristics of each. Part I of the survey (this article) provides an introduction and surveys the deterministic optimization methods that have been applied to OPF. Part II of the survey examines the recent trend towards stochastic, or non-deterministic, search techniques and hybrid methods for OPF. (orig.)

  2. Formulation and Optimization of Multiparticulate Drug Delivery System Approach for High Drug Loading.

    Shah, Neha; Mehta, Tejal; Gohel, Mukesh

    2017-08-01

    The aim of the present work was to develop and optimize multiparticulate formulation viz. pellets of naproxen by employing QbD and risk assessment approach. Mixture design with extreme vertices was applied to the formulation with high loading of drug (about 90%) and extrusion-spheronization as a process for manufacturing pellets. Independent variables chosen were level of microcrystalline cellulose (MCC)-X 1 , polyvinylpyrrolidone K-90 (PVP K-90)-X 2 , croscarmellose sodium (CCS)-X 3 , and polacrilin potassium (PP)-X 4 . Dependent variables considered were disintegration time (DT)-Y 1 , sphericity-Y 2 , and percent drug release-Y 3 . The formulation was optimized based on the batches generated by MiniTab 17 software. The batch with maximum composite desirability (0.98) proved to be optimum. From the evaluation of design batches, it was observed that, even in low variation, the excipients affect the pelletization property of the blend and also the final drug release. In conclusion, pellets with high drug loading can be effectively manufactured and optimized systematically using QbD approach.

  3. Optimization and formulation design of carbopol loaded Piroxicam gel using novel penetration enhancers.

    Chaudhary, Hema; Rohilla, Ajay; Rathee, Permender; Kumar, Vikash

    2013-04-01

    The aim of the study was to develop and optimize Piroxicam transdermal gel formulation using three-factor, three-level Box-Behnken design by deriving a second-order polynomial equation to construct contour plots for prediction of responses as three selected independent variables with ratio of carbopol 974 (X1), ratio of propylene glycol (PG) (X2) and ratio of ethanol (X3). The dependent variables studied were the skin permeation rate of piroxicam (Y1), viscosity of the gel (Y2) and pH of the gel (Y3). Response surface plots were drawn, statistical validity of the polynomials was established to find the compositions of optimized formulation which was evaluated using the vertical Franz-type diffusion cell. The permeation rate of piroxicam increased proportionally with ethanol concentration but decreased with polymer concentration. The design demonstrated the role of the derived polynomial equation and contour plots in predicting the values of dependent variables for the preparation and optimization of gel formulation. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Formulation and Optimization of Eudragit RS PO-Tenofovir Nanocarriers Using Box-Behnken Experimental Design

    Kefilwe Matlhola

    2015-01-01

    Full Text Available The objective of present study was to develop an optimized polymeric nanoparticle system for the antiretroviral drug tenofovir. A modified nanoprecipitation method was used to prepare Eudragit RS PO nanoparticles of the drug. The effect of amount of polymer, surfactant concentration, and sonication time on particle size, particle distribution, encapsulation efficiency (EE, and zeta potential were assessed and optimized utilizing a three-factor, three-level Box-Behnken Design (BBD of experiment. Fifteen formulations of nanoparticles were prepared as per BBD and evaluated for particle size, polydispersity index (PDI, EE, and zeta potential. The results showed that the measured mean particle sizes were in the range of 233 to 499 nm, PDI ranged from 0.094 to 0.153, average zeta potential ranged from −19.9 to −45.8 mV, and EE ranged between 98 and 99%. The optimized formulation was characterized for in vitro drug release and structural characterization. The mean particle size of this formulation was 233 nm with a PDI of 0.0107. It had a high EE of 98% and average zeta potential of −35 mV, an indication of particle stability. The FTIR showed some noncovalent interactions between the drug and polymer but a sustained release was observed in vitro for up to 80 hours.

  5. Optimization of primaquine diphosphate tablet formulation for controlled drug release using the mixture experimental design.

    Duque, Marcelo Dutra; Kreidel, Rogério Nepomuceno; Taqueda, Maria Elena Santos; Baby, André Rolim; Kaneko, Telma Mary; Velasco, Maria Valéria Robles; Consiglieri, Vladi Olga

    2013-01-01

    A tablet formulation based on hydrophilic matrix with a controlled drug release was developed, and the effect of polymer concentrations on the release of primaquine diphosphate was evaluated. To achieve this purpose, a 20-run, four-factor with multiple constraints on the proportions of the components was employed to obtain tablet compositions. Drug release was determined by an in vitro dissolution study in phosphate buffer solution at pH 6.8. The polynomial fitted functions described the behavior of the mixture on simplex coordinate systems to study the effects of each factor (polymer) on tablet characteristics. Based on the response surface methodology, a tablet composition was optimized with the purpose of obtaining a primaquine diphosphate release closer to a zero order kinetic. This formulation released 85.22% of the drug for 8 h and its kinetic was studied regarding to Korsmeyer-Peppas model, (Adj-R(2) = 0.99295) which has confirmed that both diffusion and erosion were related to the mechanism of the drug release. The data from the optimized formulation were very close to the predictions from statistical analysis, demonstrating that mixture experimental design could be used to optimize primaquine diphosphate dissolution from hidroxypropylmethyl cellulose and polyethylene glycol matrix tablets.

  6. Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems - Poisson and convection-diffusion control

    Axelsson, Owe; Farouq, S.; Neytcheva, M.

    2016-01-01

    Roč. 73, č. 3 (2016), s. 631-633 ISSN 1017-1398 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods Subject RIV: BA - General Mathematics Impact factor: 1.241, year: 2016 http://link.springer.com/article/10.1007%2Fs11075-016-0111-1

  7. Optimizing the taste-masked formulation of acetaminophen using sodium caseinate and lecithin by experimental design.

    Hoang Thi, Thanh Huong; Lemdani, Mohamed; Flament, Marie-Pierre

    2013-09-10

    In a previous study of ours, the association of sodium caseinate and lecithin was demonstrated to be promising for masking the bitterness of acetaminophen via drug encapsulation. The encapsulating mechanisms were suggested to be based on the segregation of multicomponent droplets occurring during spray-drying. The spray-dried particles delayed the drug release within the mouth during the early time upon administration and hence masked the bitterness. Indeed, taste-masking is achieved if, within the frame of 1-2 min, drug substance is either not released or the released amount is below the human threshold for identifying its bad taste. The aim of this work was (i) to evaluate the effect of various processing and formulation parameters on the taste-masking efficiency and (ii) to determine the optimal formulation for optimal taste-masking effect. Four investigated input variables included inlet temperature (X1), spray flow (X2), sodium caseinate amount (X3) and lecithin amount (X4). The percentage of drug release amount during the first 2 min was considered as the response variable (Y). A 2(4)-full factorial design was applied and allowed screening for the most influential variables i.e. sodium caseinate amount and lecithin amount. Optimizing these two variables was therefore conducted by a simplex approach. The SEM and DSC results of spray-dried powder prepared under optimal conditions showed that drug seemed to be well encapsulated. The drug release during the first 2 min significantly decreased, 7-fold less than the unmasked drug particles. Therefore, the optimal formulation that performed the best taste-masking effect was successfully achieved. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Optimization of natural lipstick formulation based on pitaya (Hylocereus polyrhizus) seed oil using D-optimal mixture experimental design.

    Kamairudin, Norsuhaili; Gani, Siti Salwa Abd; Masoumi, Hamid Reza Fard; Hashim, Puziah

    2014-10-16

    The D-optimal mixture experimental design was employed to optimize the melting point of natural lipstick based on pitaya (Hylocereus polyrhizus) seed oil. The influence of the main lipstick components-pitaya seed oil (10%-25% w/w), virgin coconut oil (25%-45% w/w), beeswax (5%-25% w/w), candelilla wax (1%-5% w/w) and carnauba wax (1%-5% w/w)-were investigated with respect to the melting point properties of the lipstick formulation. The D-optimal mixture experimental design was applied to optimize the properties of lipstick by focusing on the melting point with respect to the above influencing components. The D-optimal mixture design analysis showed that the variation in the response (melting point) could be depicted as a quadratic function of the main components of the lipstick. The best combination of each significant factor determined by the D-optimal mixture design was established to be pitaya seed oil (25% w/w), virgin coconut oil (37% w/w), beeswax (17% w/w), candelilla wax (2% w/w) and carnauba wax (2% w/w). With respect to these factors, the 46.0 °C melting point property was observed experimentally, similar to the theoretical prediction of 46.5 °C. Carnauba wax is the most influential factor on this response (melting point) with its function being with respect to heat endurance. The quadratic polynomial model sufficiently fit the experimental data.

  9. Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems

    R. Venkata Rao

    2016-01-01

    Full Text Available The teaching-learning-based optimization (TLBO algorithm is finding a large number of applications in different fields of engineering and science since its introduction in 2011. The major applications are found in electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics, chemistry, biotechnology and economics. This paper presents a review of applications of TLBO algorithm and a tutorial for solving the unconstrained and constrained optimization problems. The tutorial is expected to be useful to the beginners.

  10. Design of a Circularly Polarized Galileo E6-Band Textile Antenna by Dedicated Multiobjective Constrained Pareto Optimization

    Arnaut Dierck

    2015-01-01

    Full Text Available Designing textile antennas for real-life applications requires a design strategy that is able to produce antennas that are optimized over a wide bandwidth for often conflicting characteristics, such as impedance matching, axial ratio, efficiency, and gain, and, moreover, that is able to account for the variations that apply for the characteristics of the unconventional materials used in smart textile systems. In this paper, such a strategy, incorporating a multiobjective constrained Pareto optimization, is presented and applied to the design of a Galileo E6-band antenna with optimal return loss and wide-band axial ratio characteristics. Subsequently, different prototypes of the optimized antenna are fabricated and measured to validate the proposed design strategy.

  11. Optimization and characterization of spray-dried IgG formulations: a design of experiment approach.

    Faghihi, Homa; Najafabadi, Abdolhosein Rouholamini; Vatanara, Alireza

    2017-10-24

    The purpose of the present study is to optimize a spray-dried formulation as a model antibody regarding stability and aerodynamic property for further aerosol therapy of this group of macromolecules. A three-factor, three-level, Box-Behnken design was employed milligrams of Cysteine (X 1 ), Trehalose (X 2 ), and Tween 20 (X 3 ) as independent variables. The dependent variables were quantified and the optimized formulation was prepared accordingly. SEC-HPLC and FTIR-spectroscopy were conducted to evaluate the molecular and structural status of spray-dried preparations. Particle characterization of optimized sample was performed with the aid of DSC, SEM, and TSI examinations. Experimental responses of a total of 17 formulations resulted in yield values, (Y 1 ), ranging from 21.1 ± 0.2 to 40.2 ± 0.1 (%); beta-sheet content, (Y 2 ), from 66.22 ± 0.19 to 73.78 ± 0.26 (%); amount of aggregation following process, (Y 3 ), ranging from 0.11 ± 0.03 to 0.95 ± 0.03 (%); and amount of aggregation upon storage, (Y 4 ), from 0.81 ± 0.01 to 3.13 ± 0.64 (%) as dependent variables. Results-except for those of the beta sheet content-were fitted to quadratic models describing the inherent relationship between main factors. Co-application of Cysteine and Tween 20 preserved antibody molecules from molecular degradation and improved immediate and accelerated stability of spry-dried antibodies. Validation of the optimization study indicated high degree of prognostic ability of response surface methodology in preparation of stable spray-dried IgG. Graphical abstract Spray drying of IgG in the presence of Trehalose, Cysteine and Tween 20.

  12. Dynamic Convex Duality in Constrained Utility Maximization

    Li, Yusong; Zheng, Harry

    2016-01-01

    In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual problems in terms of FBSDEs plus additional conditions. Such formulation then allows us to explicitly characterize the primal optimal control as a function of the adjoint process coming from the dual FBSDEs in a dynamic fashion and vice versa. Moreover, we also...

  13. Lycopene in Beverage Emulsions: Optimizing Formulation Design and Processing Effects for Enhanced Delivery

    Erika Meroni

    2018-02-01

    Full Text Available Lycopene is a desired ingredient in food formulations, yet its beneficial effects on human health remain largely underexploited due to its poor chemical stability and bioavailability. Oil-in-water emulsions may offer multiple advantages for the incorporation and delivery of this carotenoid species. Engineering and processing aspects for the development of emulsion-based delivery systems are of paramount importance for maintaining the structural integrity of lycopene. The selection of emulsifiers, pH, temperature, oil phase, particle size, homogenization conditions and presence of other antioxidants are major determinants for enhancing lycopene stability and delivery from a food emulsion. Process and formulation optimization of the delivery system is product-specific and should be tailored accordingly. Further research is required to better understand the underlying mechanisms of lycopene absorption by the human digestive system.

  14. Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging through Chance Constrained Mixed-Integer Programming

    Liu, Zhaoxi; Wu, Qiuwei; Oren, Shmuel S.

    2017-01-01

    This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming designed to alleviate the possible congestion in the future distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic...

  15. Formulation and optimization of mucoadhesive microemulsion containing mirtazapine for intranasal delivery

    Hetal P Thakkar

    2014-01-01

    Full Text Available Background: Mirtazapine, an antidepressant drug, has absolute bioavailability of only 50% due to high first pass metabolism. Aim: The purpose of this study was to develop and optimize mucoadhesive microemulsion containing mirtazapine for intranasal delivery. Materials and Methods: Based on solubility study, Capmul Medium chain Monoglyceride, Tween 80 and polyethylene glycol (PEG 400 were selected as oil, surfactant and co surfactant respectively. Microemulsions were prepared using water titration method. 3:1% w/w ratio (Tween 80: PEG 400 was selected for formulation development. The prepared microemulsions were optimized for globule size, zeta potential, % transmittance and polydispersity index. The optimized batch was further characterized for % drug content, conductivity and transmission electron microscopy. Results and Conclusion: All the parameters showed the suitability of microemulsion of mirtazapine for intranasal delivery. Chitosan (0.5% w/w was used as a polymer for the preparation of mucoadhesive microemulsion to enhance the retention time in the nasal mucosa. Results of nasal toxicity study using excised sheep nasal mucosa showed comparatively no damage to epithelium and so formulation was considered safe for nasal administration. mirtazapine mucoadhesive microemulsion showed the highest percentage of diffusion (57.11 ± 0.710% after 210 min during in-vitro drug diffusion study through sheep nasal mucosa, followed by mirtazapine microemulsion (46.08 ± 0.674% and finally by mirtazapine solution (17.63 ± 0.612%.

  16. Optimizing Oral Bioavailability in Drug Discovery: An Overview of Design and Testing Strategies and Formulation Options.

    Aungst, Bruce J

    2017-04-01

    For discovery teams working toward new, orally administered therapeutic agents, one requirement is to attain adequate systemic exposure after oral dosing, which is best accomplished when oral bioavailability is optimized. This report summarizes the bioavailability challenges currently faced in drug discovery, and the design and testing methods and strategies currently utilized to address the challenges. Profiling of discovery compounds usually includes separate assessments of solubility, permeability, and susceptibility to first-pass metabolism, which are the 3 most likely contributors to incomplete oral bioavailability. An initial assessment of absorption potential may be made computationally, and high throughput in vitro assays are typically performed to prioritize compounds for in vivo studies. The initial pharmacokinetic study is a critical decision point in compound evaluation, and the importance of the effect the dosing vehicle or formulation can have on oral bioavailability, especially for poorly water soluble compounds, is emphasized. Dosing vehicles and bioavailability-enabling formulations that can be used for discovery and preclinical studies are described. Optimizing oral bioavailability within a chemical series or for a lead compound requires identification of the barrier limiting bioavailability, and methods used for this purpose are outlined. Finally, a few key guidelines are offered for consideration when facing the challenges of optimizing oral bioavailability in drug discovery. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  17. Formulation and optimization of itraconazole polymeric lipid hybrid nanoparticles (Lipomer) using Box Behnken design.

    Gajra, Balaram; Dalwadi, Chintan; Patel, Ravi

    2015-01-21

    The objective of the study was to formulate and to investigate the combined influence of 3 independent variables in the optimization of Polymeric lipid hybrid nanoparticles (PLHNs) (Lipomer) containing hydrophobic antifungal drug Itraconazole and to improve intestinal permeability. The Polymeric lipid hybrid nanoparticle formulation was prepared by the emulsification solvent evaporation method and 3 factor 3 level Box Behnken statistical design was used to optimize and derive a second order polynomial equation and construct contour plots to predict responses. Biodegradable Polycaprolactone, soya lecithin and Poly vinyl alcohol were used to prepare PLHNs. The independent variables selected were lipid to polymer ratio (X1) Concentration of surfactant (X2) Concentration of the drug (X3). The Box-Behnken design demonstrated the role of the derived equation and contour plots in predicting the values of dependent variables for the preparation and optimization of Itraconazole PLHNs. Itraconazole PLHNs revealed nano size (210 ± 1.8 nm) with an entrapment efficiency of 83 ± 0.6% and negative zeta potential of -11.7 mV and also enhance the permeability of itraconazole as the permeability coefficient (Papp) and the absorption enhancement ratio was higher. The tunable particle size, surface charge, and favourable encapsulation efficiency with a sustained drug release profile of PLHNs suggesting that it could be promising system envisioned to increase the bioavailability by improving intestinal permeability through lymphatic uptake, M cell of payer's patch or paracellular pathway which was proven by confocal microscopy.

  18. Formulation and Evaluation of Optimized Oxybenzone Microsponge Gel for Topical Delivery

    Atmaram P. Pawar

    2015-01-01

    Full Text Available Background. Oxybenzone, a broad spectrum sunscreen agent widely used in the form of lotion and cream, has been reported to cause skin irritation, dermatitis, and systemic absorption. Aim. The objective of the present study was to formulate oxybenzone loaded microsponge gel for enhanced sun protection factor with reduced toxicity. Material and Method. Microsponge for topical delivery of oxybenzone was successfully prepared by quasiemulsion solvent diffusion method. The effects of ethyl cellulose and dichloromethane were optimized by the 32 factorial design. The optimized microsponges were dispersed into the hydrogel and further evaluated. Results. The microsponges were spherical with pore size in the range of 0.10–0.22 µm. The optimized formulation possesses the particle size and entrapment efficiency of 72 ± 0.77 µm and 96.9 ± 0.52%, respectively. The microsponge gel showed the controlled release and was nonirritant to the rat skin. In creep recovery test it had shown highest recovery indicating elasticity. The controlled release of oxybenzone from microsponge and barrier effect of gel result in prolonged retention of oxybenzone with reduced permeation activity. Conclusion. Evaluation study revealed remarkable and enhanced topical retention of oxybenzone for prolonged period of time. It also showed the enhanced sun protection factor compared to the marketed preparation with reduced irritation and toxicity.

  19. A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

    Zhang, Chenglong; Guo, Ping

    2017-10-01

    The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

  20. Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

    Xing Liu

    2014-12-01

    Full Text Available Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.

  1. Energy optimization for upstream data transfer in 802.15.4 beacon-enabled star formulation

    Liu, Hua; Krishnamachari, Bhaskar

    2008-08-01

    Energy saving is one of the major concerns for low rate personal area networks. This paper models energy consumption for beacon-enabled time-slotted media accessing control cooperated with sleeping scheduling in a star network formulation for IEEE 802.15.4 standard. We investigate two different upstream (data transfer from devices to a network coordinator) strategies: a) tracking strategy: the devices wake up and check status (track the beacon) in each time slot; b) non-tracking strategy: nodes only wake-up upon data arriving and stay awake till data transmitted to the coordinator. We consider the tradeoff between energy cost and average data transmission delay for both strategies. Both scenarios are formulated as optimization problems and the optimal solutions are discussed. Our results show that different data arrival rate and system parameters (such as contention access period interval, upstream speed etc.) result in different strategies in terms of energy optimization with maximum delay constraints. Hence, according to different applications and system settings, different strategies might be chosen by each node to achieve energy optimization for both self-interested view and system view. We give the relation among the tunable parameters by formulas and plots to illustrate which strategy is better under corresponding parameters. There are two main points emphasized in our results with delay constraints: on one hand, when the system setting is fixed by coordinator, nodes in the network can intelligently change their strategies according to corresponding application data arrival rate; on the other hand, when the nodes' applications are known by the coordinator, the coordinator can tune the system parameters to achieve optimal system energy consumption.

  2. Lower irritation microemulsion-based rotigotine gel: formulation optimization and in vitro and in vivo studies.

    Wang, Zheng; Mu, Hong-Jie; Zhang, Xue-Mei; Ma, Peng-Kai; Lian, Sheng-Nan; Zhang, Feng-Pu; Chu, Sheng-Ying; Zhang, Wen-Wen; Wang, Ai-Ping; Wang, Wen-Yan; Sun, Kao-Xiang

    2015-01-01

    Rotigotine is a potent and selective D1, D2, and D3 dopaminergic receptor agonist. Due to an extensive first-pass effect, it has a very low oral bioavailability (approximately 0.5% in rats). The present investigation aimed to develop a microemulsion-based hydrogel for transdermal rotigotine delivery with lower application site reactions. Pseudoternary phase diagrams were constructed to determine the region of oil in water (o/w)-type microemulsion. Central composite design was used to support the pseudoternary phase diagrams and to select homogeneous and stable microemulsions with an optimal amount of rotigotine permeation within 24 hours. In vitro skin permeation experiments were performed, using Franz diffusion cells, to compare rotigotine-loaded microemulsions with rotigotine solutions in oil. The optimized formulation was used to prepare a microemulsion-based hydrogel, which was subjected to bioavailability and skin irritancy studies. The selected formulations of rotigotine-loaded microemulsions had enhanced flux and permeation coefficients compared with rotigotine in oil. The optimum microemulsion contained 68% water, 6.8% Labrafil(®), 13.44% Cremophor(®) RH40, 6.72% Labrasol(®), and 5.04% Transcutol(®) HP; the drug-loading rate was 2%. To form a microemulsion gel, 1% Carbomer 1342 was added to the microemulsion. The bioavailability of the rotigotine-loaded microemulsion gel was 105.76%±20.52% with respect to the marketed rotigotine patch (Neupro(®)). The microemulsion gel irritated the skin less than Neupro. A rotigotine microemulsion-based hydrogel was successfully developed, and an optimal formulation for drug delivery was identified. This product could improve patient compliance and have broad marketability.

  3. Formulation strategies for optimizing the morphology of polymeric bulk heterojunction organic solar cells: a brief review

    Vongsaysy, Uyxing; Bassani, Dario M.; Servant, Laurent; Pavageau, Bertrand; Wantz, Guillaume; Aziz, Hany

    2014-01-01

    Polymeric bulk heterojunction (BHJ) organic solar cells represent one of the most promising technologies for renewable energy with a low fabrication cost. Control over BHJ morphology is one of the key factors in obtaining high-efficiency devices. This review focuses on formulation strategies for optimizing the BHJ morphology. We address how solvent choice and the introduction of processing additives affect the morphology. We also review a number of recent studies concerning prediction methods that utilize the Hansen solubility parameters to develop efficient solvent systems.

  4. Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design

    Chocat Rudy

    2015-01-01

    Full Text Available The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise. The update mechanisms of the parametrized distribution used to generate the candidate solutions are modified. The constraint handling method allows to reduce the semi-principal axes of the probable research ellipsoid in the directions violating the constraints. The proposed approach is compared to existing approaches on three analytic optimization problems to highlight the efficiency and the robustness of the algorithm. The proposed method is used to design a two stage solid propulsion launch vehicle.

  5. Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function

    Pearson, John W.; Stoll, Martin; Wathen, Andrew J.

    2012-01-01

    Optimal control problems with partial differential equations as constraints play an important role in many applications. The inclusion of bound constraints for the state variable poses a significant challenge for optimization methods. Our focus here

  6. Optimization of Natural Lipstick Formulation Based on Pitaya (Hylocereus polyrhizus Seed Oil Using D-Optimal Mixture Experimental Design

    Norsuhaili Kamairudin

    2014-10-01

    Full Text Available The D-optimal mixture experimental design was employed to optimize the melting point of natural lipstick based on pitaya (Hylocereus polyrhizus seed oil. The influence of the main lipstick components—pitaya seed oil (10%–25% w/w, virgin coconut oil (25%–45% w/w, beeswax (5%–25% w/w, candelilla wax (1%–5% w/w and carnauba wax (1%–5% w/w—were investigated with respect to the melting point properties of the lipstick formulation. The D-optimal mixture experimental design was applied to optimize the properties of lipstick by focusing on the melting point with respect to the above influencing components. The D-optimal mixture design analysis showed that the variation in the response (melting point could be depicted as a quadratic function of the main components of the lipstick. The best combination of each significant factor determined by the D-optimal mixture design was established to be pitaya seed oil (25% w/w, virgin coconut oil (37% w/w, beeswax (17% w/w, candelilla wax (2% w/w and carnauba wax (2% w/w. With respect to these factors, the 46.0 °C melting point property was observed experimentally, similar to the theoretical prediction of 46.5 °C. Carnauba wax is the most influential factor on this response (melting point with its function being with respect to heat endurance. The quadratic polynomial model sufficiently fit the experimental data.

  7. Optimized and validated flow-injection spectrophotometric analysis of topiramate, piracetam and levetiracetam in pharmaceutical formulations.

    Hadad, Ghada M; Abdel-Salam, Randa A; Emara, Samy

    2011-12-01

    Application of a sensitive and rapid flow injection analysis (FIA) method for determination of topiramate, piracetam, and levetiracetam in pharmaceutical formulations has been investigated. The method is based on the reaction with ortho-phtalaldehyde and 2-mercaptoethanol in a basic buffer and measurement of absorbance at 295 nm under flow conditions. Variables affecting the determination such as sample injection volume, pH, ionic strength, reagent concentrations, flow rate of reagent and other FIA parameters were optimized to produce the most sensitive and reproducible results using a quarter-fraction factorial design, for five factors at two levels. Also, the method has been optimized and fully validated in terms of linearity and range, limit of detection and quantitation, precision, selectivity and accuracy. The method was successfully applied to the analysis of pharmaceutical preparations.

  8. Enhanced Ungual Permeation of Terbinafine HCl Delivered Through Liposome-Loaded Nail Lacquer Formulation Optimized by QbD Approach.

    Shah, Viral H; Jobanputra, Amee

    2018-01-01

    The present investigation focused on developing, optimizing, and evaluating a novel liposome-loaded nail lacquer formulation for increasing the transungual permeation flux of terbinafine HCl for efficient treatment of onychomycosis. A three-factor, three-level, Box-Behnken design was employed for optimizing process and formulation parameters of liposomal formulation. Liposomes were formulated by thin film hydration technique followed by sonication. Drug to lipid ratio, sonication amplitude, and sonication time were screened as independent variables while particle size, PDI, entrapment efficiency, and zeta potential were selected as quality attributes for liposomal formulation. Multiple regression analysis was employed to construct a second-order quadratic polynomial equation and contour plots. Design space (overlay plot) was generated to optimize a liposomal system, with software-suggested levels of independent variables that could be transformed to desired responses. The optimized liposome formulation was characterized and dispersed in nail lacquer which was further evaluated for different parameters. Results depicted that the optimized terbinafine HCl-loaded liposome formulation exhibited particle size of 182 nm, PDI of 0.175, zeta potential of -26.8 mV, and entrapment efficiency of 80%. Transungual permeability flux of terbinafine HCl through liposome-dispersed nail lacquer formulation was observed to be significantly higher in comparison to nail lacquer with a permeation enhancer. The developed formulation was also observed to be as efficient as pure drug dispersion in its antifungal activity. Thus, it was concluded that the developed formulation can serve as an efficient tool for enhancing the permeability of terbinafine HCl across human nail plate thereby improving its therapeutic efficiency.

  9. Application of hanging drop technique to optimize human IgG formulations.

    Li, Guohua; Kasha, Purna C; Late, Sameer; Banga, Ajay K

    2010-01-01

    The purpose of this work is to assess the hanging drop technique in screening excipients to develop optimal formulations for human immunoglobulin G (IgG). A microdrop of human IgG and test solution hanging from a cover slide and undergoing vapour diffusion was monitored by a stereomicroscope. Aqueous solutions of IgG in the presence of different pH, salt concentrations and excipients were prepared and characterized. Low concentration of either sodium/potassium phosphate or McIlvaine buffer favoured the solubility of IgG. Addition of sucrose favoured the stability of this antibody while addition of NaCl caused more aggregation. Antimicrobial preservatives were also screened and a complex effect at different buffer conditions was observed. Dynamic light scattering, differential scanning calorimetry and size exclusion chromatography studies were performed to further validate the results. In conclusion, hanging drop is a very easy and effective approach to screen protein formulations in the early stage of formulation development.

  10. Formulation optimization of gentamicin loaded Eudragit RS100 microspheres using factorial design study.

    Singh, Deependra; Saraf, Swarnlata; Dixit, Vinod Kumar; Saraf, Shailendra

    2008-04-01

    Gentamicin-Eudragit RS100 microspheres were prepared by modified double emulsion method. A 3(2) full factorial experiment was designed to study the effects of the composition of outer aqueous phase in terms of amount of glycerol (viscosity effect) and sodium chloride (osmotic pressure gradient effect) on the entrapment efficiency and % yield and microsphere size. The results of analysis of variance test for responses measured indicated that the test is significant (p>0.05). The contribution of sodium chloride concentration was found to be higher on entrapment efficiency and % yield, whereas glycerol produced significant effect on the mean diameter of microspheres. Microspheres demonstrated spherical particles in the size range of 33.24-60.43 microm. In vitro release profile of optimized formulation demonstrated sustained release for 24 h following Higuchi kinetics. Finally, drug bioactivity was found to remain intact after microencapsulation. Response surface graphs are presented to examine the effects of independent variables on the responses studied. Thus, by formulation design important parameters affecting formulation characteristics of gentamicin loaded Eudragit RS100 microspheres can be identified for controlled delivery with desirable characters in terms of maximum entrapment and yield.

  11. Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

    Nebojsa Bacanin

    2014-01-01

    portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

  12. SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

    Wei, J [City College of New York, New York, NY (United States); Chao, M [The Mount Sinai Medical Center, New York, NY (United States)

    2016-06-15

    Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

  13. SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

    Wei, J; Chao, M

    2016-01-01

    Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

  14. Formulation development and optimization of palm kernel oil esters-based nanoemulsions containing sodium diclofenac.

    Rezaee, Malahat; Basri, Mahiran; Rahman, Raja Noor Zaliha Raja Abdul; Salleh, Abu Bakar; Chaibakhsh, Naz; Karjiban, Roghayeh Abedi

    2014-01-01

    Response surface methodology was employed to study the effect of formulation composition variables, water content (60%-80%, w/w) and oil and surfactant (O/S) ratio (0.17-1.33), as well as high-shear emulsification conditions, mixing rate (300-3,000 rpm) and mixing time (5-30 minutes) on the properties of sodium diclofenac-loaded palm kernel oil esters-nanoemulsions. The two response variables were droplet size and viscosity. Optimization of the conditions according to the four variables was performed for preparation of the nanoemulsions with the minimum values of particle size and viscosity. The results showed that the experimental data could be sufficiently fitted into a third-order polynomial model with multiple regression coefficients (R(2) ) of 0.938 and 0.994 for the particle size and viscosity, respectively. Water content, O/S ratio and mixing time, quadrics of all independent variables, interaction between O/S ratio and mixing rate and between mixing time and rate, as well as cubic term of water content had a significant effect (Pdiclofenac nanoemulsions were predicted to be: 71.36% water content; 0.69 O/S ratio; 950 rpm mixing rate, and 5 minute mixing time. The optimized formulation showed good storage stability in different temperatures.

  15. Formulation design and optimization for the improvement of nystatin-loaded lipid intravenous emulsion.

    Marín-Quintero, Deiry; Fernández-Campos, Francisco; Calpena-Campmany, Ana C; Montes-López, María J; Clares-Naveros, Beatriz; Del Pozo-Carrascosa, Alfonso

    2013-11-01

    Nystatin (NYS) is a polyene macrolide with broad antifungal spectrum restricted to topical use owing to its toxicity upon systemic administration. The aims of this work were the design, development, and optimization of NYS-loaded lipid emulsion for intravenous administration. A closed circuit system was designed to apply ultrasound during the elaboration of the lipid intravenous emulsions (LIEs). Additionally, a comparison with the commercially available Intralipid(®) 20% was also performed. Manufacturing conditions were optimized by factorial design. Formulations were evaluated in terms of physicochemical parameters, stability, release profile, and antimicrobial activity. The average droplet size, polydispersity index, zeta-potential, pH, and volume distribution values ranged between 192.5 and 143.0 nm, 0.170 and 0.135, -46 and -44 mV, 7.11 and 7.53, 580 and 670 nm, respectively. The selected NYS-loaded LIE (NYS-LIE54) consisted of soybean oil (30%), soybean lecithin (2%), solutol HS(®) 15 (4%), and glycerol (2.25%) was stable for at least 60 days. In vitro drug release studies of this formulation suggested a sustained-release profile. Equally, NYS-LIE54 showed the best antimicrobial activity being higher than the free drug. Thus, it could be a promising drug delivery system to treat systemic fungal infections. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

  16. Formulation optimization and evaluation of jackfruit seed starch-alginate mucoadhesive beads of metformin HCl.

    Nayak, Amit Kumar; Pal, Dilipkumar

    2013-08-01

    The present study deals with the formulation optimization of jackfruit (Artocarpus heterophyllus Lam., family: Moraceae) seed starch (JFSS)-alginate mucoadhesive beads containing metformin HCl through ionotropic gelation using 3(2) factorial design. The effect of sodium alginate to JFSS ratio and CaCl2 concentration on the drug encapsulation efficiency (DEE, %), and cumulative drug release at 10h (R10h, %) was optimized. The optimized beads containing metformin HCl showed DEE of 97.48±3.92%, R10h of 65.70±2.22%, and mean diameter of 1.16±0.11mm. The in vitro drug release from these beads was followed controlled-release (zero-order) pattern with super case-II transport mechanism. The beads were also characterized by SEM and FTIR. The swelling and degradation of these beads were influenced by pH of the test medium. The optimized beads also exhibited good mucoadhesivity and significant hypoglycemic effect in alloxan-induced diabetic rats over prolonged period after oral administration. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Mucoadhesive Hydrogel Films of Econazole Nitrate: Formulation and Optimization Using Factorial Design

    Balaram Gajra

    2014-01-01

    Full Text Available The mucoadhesive hydrogel film was prepared and optimized for the purpose of local drug delivery to oral cavity for the treatment of oral Candidiasis. The mucoadhesive hydrogel film was prepared with the poly(vinyl alcohol by freeze/thaw crosslinking technique. 32 full factorial design was employed to optimize the formulation. Number of freeze/thaw cycles (4, 6, and 8 cycles and the concentration of the poly(vinyl alcohol (10, 15, and 20% were used as the independent variables whereas time required for 50% drug release, cumulative percent of drug release at 8th hour, and “k” of zero order equation were used as the dependent variables. The films were evaluated for mucoadhesive strength, in vitro residence time, swelling study, in vitro drug release, and effectiveness against Candida albicans. The concentration of poly(vinyl alcohol and the number of freeze/thaw cycles both decrease the drug release rate. Mucoadhesive hydrogel film with 15% poly(vinyl alcohol and 7 freeze/thaw cycles was optimized. The optimized batch exhibited the sustained release of drug and the antifungal studies revealed that the drug released from the film could inhibit the growth of Candida albicans for 12 hours.

  18. Quality by design approach for formulation, evaluation and statistical optimization of diclofenac-loaded ethosomes via transdermal route.

    Jain, Shashank; Patel, Niketkumar; Madan, Parshotam; Lin, Senshang

    2015-06-01

    The objective of this study was to fabricate and understand ethosomal formulations of diclofenac (DF) for enhanced anti-inflammatory activity using quality by design approach. DF-loaded ethosomal formulations were prepared using 4 × 5 full-factorial design with phosphatidylcholine:cholesterol (PC:CH) ratios ranging between 50:50 and 90:10, and ethanol concentration ranging between 0% and 30% as formulation variables. These formulations were characterized in terms of physicochemical properties and skin permeation kinetics. The interaction of formulation variables had a significant effect on both physicochemical properties and permeation kinetics. The results of multivariate regression analysis illustrated that vesicle size and elasticity of ethosomes were the dominating physicochemical properties affecting skin permeation, and could be suitably controlled by manipulation of formulation variables to optimize the formulation and enhance the skin permeation of DF-loaded ethosomes. The optimized formulation had ethanol concentration of 22.9% and PC:CH ratio of 88.4:11.6, with vesicle size of 144 ± 5 nm, zeta potential of -23.0 ± 3.76 mV, elasticity of 2.48 ± 0.75 and entrapment efficiency of 71 ± 4%. Permeation flux for the optimized formulation was 12.9 ± 1.0 µg/h cm(2), which was significantly higher than the drug-loaded conventional liposome, ethanolic or aqueous solution. The in vivo study indicated that optimized ethosomal hydrogel exhibited enhanced anti-inflammatory activity compared with liposomal and plain drug hydrogel formulations.

  19. Constrained Optimal Stochastic Control of Non-Linear Wave Energy Point Absorbers

    Sichani, Mahdi Teimouri; Chen, Jian-Bing; Kramer, Morten

    2014-01-01

    to extract energy. Constrains are enforced on the control force to prevent large structural stresses in the floater at specific hot spots with the risk of inducing fatigue damage, or because the demanded control force cannot be supplied by the actuator system due to saturation. Further, constraints...... are enforced on the motion of the floater to prevent it from hitting the bottom of the sea or to make unacceptable jumps out of the water. The applied control law, which is of the feedback type with feedback from the displacement, velocity, and acceleration of the floater, contains two unprovided gain...

  20. The Use of D-Optimal Mixture Design in Optimizing Development of Okara Tablet Formulation as a Dietary Supplement

    Mohamad Zen, Nur Izzati; Shamsudin, Rosnah

    2015-01-01

    The usage of soy is increasing year by year. It increases the problem of financial crisis due to the limited sources of soybeans. Therefore, production of oral tablets containing the nutritious leftover of soymilk production, called okara, as the main ingredient was investigated. The okara tablets were produced using the direct compression method. The percentage of okara, guar gum, microcrystalline cellulose (Avicel PH-101), and maltodextrin influenced tablets' hardness and friability which are analyzed using a D-optimal mixture design. Composition of Avicel PH-101 had positive effects for both hardness and friability tests of the tablets. Maltodextrin and okara composition had a significant positive effect on tablets' hardness, but not on percentage of friability of tablets. However, guar gum had a negative effect on both physical tests. The optimum tablet formulation was obtained: 47.0% of okara, 2.0% of guar gum, 35.0% of Avicel PH-101, and 14.0% of maltodextrin. PMID:26171418

  1. The Use of D-Optimal Mixture Design in Optimizing Development of Okara Tablet Formulation as a Dietary Supplement

    Nur Izzati Mohamad Zen

    2015-01-01

    Full Text Available The usage of soy is increasing year by year. It increases the problem of financial crisis due to the limited sources of soybeans. Therefore, production of oral tablets containing the nutritious leftover of soymilk production, called okara, as the main ingredient was investigated. The okara tablets were produced using the direct compression method. The percentage of okara, guar gum, microcrystalline cellulose (Avicel PH-101, and maltodextrin influenced tablets’ hardness and friability which are analyzed using a D-optimal mixture design. Composition of Avicel PH-101 had positive effects for both hardness and friability tests of the tablets. Maltodextrin and okara composition had a significant positive effect on tablets’ hardness, but not on percentage of friability of tablets. However, guar gum had a negative effect on both physical tests. The optimum tablet formulation was obtained: 47.0% of okara, 2.0% of guar gum, 35.0% of Avicel PH-101, and 14.0% of maltodextrin.

  2. Robust optimization methods for chance constrained, simulation-based, and bilevel problems

    Yanikoglu, I.

    2014-01-01

    The objective of robust optimization is to find solutions that are immune to the uncertainty of the parameters in a mathematical optimization problem. It requires that the constraints of a given problem should be satisfied for all realizations of the uncertain parameters in a so-called uncertainty

  3. Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

    Bistra Dilkina; Rachel Houtman; Carla P. Gomes; Claire A. Montgomery; Kevin S. McKelvey; Katherine Kendall; Tabitha A. Graves; Richard Bernstein; Michael K. Schwartz

    2016-01-01

    Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a...

  4. Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

    Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S

    2017-03-01

    Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  5. SN-38 loading capacity of hydrophobic polymer blend nanoparticles: formulation, optimization and efficacy evaluation.

    Dimchevska, Simona; Geskovski, Nikola; Petruševski, Gjorgji; Chacorovska, Marina; Popeski-Dimovski, Riste; Ugarkovic, Sonja; Goracinova, Katerina

    2017-03-01

    One of the most important problems in nanoencapsulation of extremely hydrophobic drugs is poor drug loading due to rapid drug crystallization outside the polymer core. The effort to use nanoprecipitation, as a simple one-step procedure with good reproducibility and FDA approved polymers like Poly(lactic-co-glycolic acid) (PLGA) and Polycaprolactone (PCL), will only potentiate this issue. Considering that drug loading is one of the key defining characteristics, in this study we attempted to examine whether the nanoparticle (NP) core composed of two hydrophobic polymers will provide increased drug loading for 7-Ethyl-10-hydroxy-camptothecin (SN-38), relative to NPs prepared using individual polymers. D-optimal design was applied to optimize PLGA/PCL ratio in the polymer blend and the mode of addition of the amphiphilic copolymer Lutrol ® F127 in order to maximize SN-38 loading and obtain NPs with acceptable size for passive tumor targeting. Drug/polymer and polymer/polymer interaction analysis pointed to high degree of compatibility and miscibility among both hydrophobic polymers, providing core configuration with higher drug loading capacity. Toxicity studies outlined the biocompatibility of the blank NPs. Increased in vitro efficacy of drug-loaded NPs compared to the free drug was confirmed by growth inhibition studies using SW-480 cell line. Additionally, the optimized NP formulation showed very promising blood circulation profile with elimination half-time of 7.4 h.

  6. Multi-Objective Design Optimization of an Over-Constrained Flexure-Based Amplifier

    Yuan Ni

    2015-07-01

    Full Text Available The optimizing design for enhancement of the micro performance of manipulator based on analytical models is investigated in this paper. By utilizing the established uncanonical linear homogeneous equations, the quasi-static analytical model of the micro-manipulator is built, and the theoretical calculation results are tested by FEA simulations. To provide a theoretical basis for a micro-manipulator being used in high-precision engineering applications, this paper investigates the modal property based on the analytical model. Based on the finite element method, with multipoint constraint equations, the model is built and the results have a good match with the simulation. The following parametric influences studied show that the influences of other objectives on one objective are complicated.  Consequently, the multi-objective optimization by the derived analytical models is carried out to find out the optimal solutions of the manipulator. Besides the inner relationships among these design objectives during the optimization process are discussed.

  7. Extended Information Ratio for Portfolio Optimization Using Simulated Annealing with Constrained Neighborhood

    Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi

    The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.

  8. Automatic analog IC sizing and optimization constrained with PVT corners and layout effects

    Lourenço, Nuno; Horta, Nuno

    2017-01-01

    This book introduces readers to a variety of tools for automatic analog integrated circuit (IC) sizing and optimization. The authors provide a historical perspective on the early methods proposed to tackle automatic analog circuit sizing, with emphasis on the methodologies to size and optimize the circuit, and on the methodologies to estimate the circuit’s performance. The discussion also includes robust circuit design and optimization and the most recent advances in layout-aware analog sizing approaches. The authors describe a methodology for an automatic flow for analog IC design, including details of the inputs and interfaces, multi-objective optimization techniques, and the enhancements made in the base implementation by using machine leaning techniques. The Gradient model is discussed in detail, along with the methods to include layout effects in the circuit sizing. The concepts and algorithms of all the modules are thoroughly described, enabling readers to reproduce the methodologies, improve the qual...

  9. A one-layer recurrent neural network for constrained nonsmooth optimization.

    Liu, Qingshan; Wang, Jun

    2011-10-01

    This paper presents a novel one-layer recurrent neural network modeled by means of a differential inclusion for solving nonsmooth optimization problems, in which the number of neurons in the proposed neural network is the same as the number of decision variables of optimization problems. Compared with existing neural networks for nonsmooth optimization problems, the global convexity condition on the objective functions and constraints is relaxed, which allows the objective functions and constraints to be nonconvex. It is proven that the state variables of the proposed neural network are convergent to optimal solutions if a single design parameter in the model is larger than a derived lower bound. Numerical examples with simulation results substantiate the effectiveness and illustrate the characteristics of the proposed neural network.

  10. A non-penalty recurrent neural network for solving a class of constrained optimization problems.

    Hosseini, Alireza

    2016-01-01

    In this paper, we explain a methodology to analyze convergence of some differential inclusion-based neural networks for solving nonsmooth optimization problems. For a general differential inclusion, we show that if its right hand-side set valued map satisfies some conditions, then solution trajectory of the differential inclusion converges to optimal solution set of its corresponding in optimization problem. Based on the obtained methodology, we introduce a new recurrent neural network for solving nonsmooth optimization problems. Objective function does not need to be convex on R(n) nor does the new neural network model require any penalty parameter. We compare our new method with some penalty-based and non-penalty based models. Moreover for differentiable cases, we implement circuit diagram of the new neural network. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. A one-layer recurrent neural network for constrained nonconvex optimization.

    Li, Guocheng; Yan, Zheng; Wang, Jun

    2015-01-01

    In this paper, a one-layer recurrent neural network is proposed for solving nonconvex optimization problems subject to general inequality constraints, designed based on an exact penalty function method. It is proved herein that any neuron state of the proposed neural network is convergent to the feasible region in finite time and stays there thereafter, provided that the penalty parameter is sufficiently large. The lower bounds of the penalty parameter and convergence time are also estimated. In addition, any neural state of the proposed neural network is convergent to its equilibrium point set which satisfies the Karush-Kuhn-Tucker conditions of the optimization problem. Moreover, the equilibrium point set is equivalent to the optimal solution to the nonconvex optimization problem if the objective function and constraints satisfy given conditions. Four numerical examples are provided to illustrate the performances of the proposed neural network.

  12. Optimization of the box-girder of overhead crane with constrained ...

    haroun

    Keywords: Overhead crane - Box-girder - New bat algorithm - level of ... much more efficiency and robustness compared to the genetic algorithm (GA) and PSO ...... optimization: developments, applications and resources," in Evolutionary.

  13. Reserve-Constrained Multiarea Environmental/Economic Dispatch Using Enhanced Particle Swarm Optimization

    Wang, Lingfeng; Singh, Chanan

    2007-01-01

    Source: Swarm Intelligence: Focus on Ant and Particle Swarm Optimization, Book edited by: Felix T. S. Chan and Manoj Kumar Tiwari, ISBN 978-3-902613-09-7, pp. 532, December 2007, Itech Education and Publishing, Vienna, Austria

  14. Direct Speed Control of PMSM Drive Using SDRE and Convex Constrained Optimization

    Šmídl, V.; Janouš, Š.; Adam, Lukáš; Peroutka, Z.

    2018-01-01

    Roč. 65, č. 1 (2018), s. 532-542 ISSN 1932-4529 Grant - others:GA MŠk(CZ) LO1607 Institutional support: RVO:67985556 Keywords : Velocity control * Optimization * Stators * Voltage control * Predictive control * Optimal control * Rotors Subject RIV: BD - Theory of Information Impact factor: 10.710, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0481225.pdf

  15. Constrained Optimization via Stochastic approximation with a simultaneous perturbation gradient approximation

    Sadegh, Payman

    1997-01-01

    This paper deals with a projection algorithm for stochastic approximation using simultaneous perturbation gradient approximation for optimization under inequality constraints where no direct gradient of the loss function is available and the inequality constraints are given as explicit functions...... of the optimization parameters. It is shown that, under application of the projection algorithm, the parameter iterate converges almost surely to a Kuhn-Tucker point, The procedure is illustrated by a numerical example, (C) 1997 Elsevier Science Ltd....

  16. Optimal Coordinated EV Charging with Reactive Power Support in Constrained Distribution Grids

    Paudyal, Sumit; Ceylan, Oğuzhan; Bhattarai, Bishnu P.; Myers, Kurt S.

    2017-07-01

    Electric vehicle (EV) charging/discharging can take place in any P-Q quadrants, which means EVs could support reactive power to the grid while charging the battery. In controlled charging schemes, distribution system operator (DSO) coordinates with the charging of EV fleets to ensure grid’s operating constraints are not violated. In fact, this refers to DSO setting upper bounds on power limits for EV charging. In this work, we demonstrate that if EVs inject reactive power into the grid while charging, DSO could issue higher upper bounds on the active power limits for the EVs for the same set of grid constraints. We demonstrate the concept in an 33-node test feeder with 1,500 EVs. Case studies show that in constrained distribution grids in coordinated charging, average costs of EV charging could be reduced if the charging takes place in the fourth P-Q quadrant compared to charging with unity power factor.

  17. Optimization of formulation and processing of Moringa oleifera and spirulina complex tablets.

    Zheng, Yi; Zhu, Fan; Lin, Dan; Wu, Jun; Zhou, Yichao; Mark, Bohn

    2017-01-01

    Objective: To prepare a more comprehensive nutrition, more balanced proportion of natural nutritional supplement tablets with Moringa oleifera leaves and spirulina the two nutrients which have complementary natural food ingredients. Method: On the basis of research M. oleifera leaves with spirulina nutrient composition was determined on M. oleifera leaves and spirulina ratio of raw materials, and the choice of microcrystalline cellulose, sodium salt of caboxy methyl cellulose(CMC),magnesium stearate excipient, through single factor and orthogonal experiment, selecting the best formula tablets prepared by powder direct compression technology, for preparation of M. oleifera and spirulina complex tablets. Results: The best ratio of raw material for the M. oleifera leaves powder: spirulina powder was 7:3, the best raw materials for the tablet formulation was 88.5%, 8.0% microcrystalline cellulose, CMC 2.0%, stearin magnesium 1.5%, the optimum parameters for the raw material crushing 200-300 mesh particle size, moisture content of 7%, tableting pressure 40 kN. Conclusion: Through formulation and process optimization, we can prepare more comprehensive and balanced nutrition M. oleifera and spirulina complex tablets, its sheet-shaped appearance, piece weight variation, hardness, friability, disintegration and other indicators have reached the appropriate quality requirements.

  18. Optimization of gluten-free formulations for French-style breads.

    Mezaize, S; Chevallier, S; Le Bail, A; de Lamballerie, M

    2009-04-01

    The formulation of gluten-free bread, which will be suitable for patients with coeliac disease, was optimized to provide bread similar to French bread. The effects of the presence of hydrocolloids and the substitution of the flour basis by flour or proteins from different sources were studied. The added ingredients were (1) hydrocolloids (carboxymethylcellulose [CMC], guar gum, hydroxypropylmethylcellulose [HPMC], and xanthan gum), and (2) substitutes (buckwheat flour, whole egg powder, and whey proteins). The bread quality parameters measured were specific volume, dry matter of bread, crust color, crumb hardness, and gas cell size distribution. Specific volume was increased by guar gum and HPMC. Breads with guar gum had color characteristics similar to French bread. Hardness decreased with the addition of hydrocolloids, especially HPMC and guar. Breads with guar gum had the most heterogeneous cell size distribution, and guar gum was therefore selected for further formulations. Bread prepared with buckwheat flour had improved quality: an increased specific volume, a softer texture, color characteristics, and gas-cell size distribution similar to French bread. Bread with 1.9% guar gum (w/w, total flour basis) and 5% buckwheat flour (of all flours and substitutes) mimicked French bread quality attributes.

  19. Optimal path planning for single and multiple aircraft using a reduced order formulation

    Twigg, Shannon S.

    High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.

  20. Formulation and Optimization of Oral Mucoadhesive Patches of Myrtus Communis by Box Behnken Design.

    Hashemi, Mahbubeh; Ramezani, Vahid; Seyedabadi, Mohammad; Ranjbar, Ali Mohamad; Jafari, Hossein; Honarvar, Mina; Fanaei, Hamed

    2017-09-01

    Purpose: Recurrent aphthous stomatitis (RAS) is the most common painful ulcerative disease of oral mucosa happening in ~20% of people. Aimed to develop Myrtus communis L. (Myrtle) containing oral patches, we applied box-behnken design to evaluate the effect of polymers such as Polyvinyl pyrrolidone (PVP), Gelatin, Methylcellulose (MC) and Pectin. Methods: The patches properties such as tensile strength, folding endurance, swelling index, thickness, mucoadhesive strength and the pattern of myrtle release were evaluated as dependent variables. Then, the model was adjusted according to the best fitted equation with box behnken design. Results: The results indicated that preparation of myrtle patch with hydrophilic polymers showed the disintegration time up to 24h and more. Using of polyvinyl pyrrolidone as a water soluble polymer and a pore-former polymer led to faster release of soluble materials from the patch to 29 (min -1 ). Also it decreases swelling index by increasing the patch disintegration. Gelatin and Pectin, with rigid matrix and water interaction properties, decreased the swelling ratio. Pectin increased the tensile strength, but gelatin produced an opposite effect. Thinner Myrtle patch (about 28µm) was obtained by formulation of methyl cellulose with equal ratio with polyvinyl pyrrolidone or gelatin. Conclusion: Altogether, the analysis showed that the optimal formulation was achieved with of 35.04 mg of Gelatin, 7.22 mg of Pectin, 7.20 mg of polyvinyl pyrrolidone, 50.52 mg of methyl cellulose and 20 mg of Myrtle extract.

  1. Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators

    Kiran Teeparthi

    2017-04-01

    Full Text Available In this paper, a new low level with teamwork heterogeneous hybrid particle swarm optimization and artificial physics optimization (HPSO-APO algorithm is proposed to solve the multi-objective security constrained optimal power flow (MO-SCOPF problem. Being engaged with the environmental and total production cost concerns, wind energy is highly penetrating to the main grid. The total production cost, active power losses and security index are considered as the objective functions. These are simultaneously optimized using the proposed algorithm for base case and contingency cases. Though PSO algorithm exhibits good convergence characteristic, fails to give near optimal solution. On the other hand, the APO algorithm shows the capability of improving diversity in search space and also to reach a near global optimum point, whereas, APO is prone to premature convergence. The proposed hybrid HPSO-APO algorithm combines both individual algorithm strengths, to get balance between global and local search capability. The APO algorithm is improving diversity in the search space of the PSO algorithm. The hybrid optimization algorithm is employed to alleviate the line overloads by generator rescheduling during contingencies. The standard IEEE 30-bus and Indian 75-bus practical test systems are considered to evaluate the robustness of the proposed method. The simulation results reveal that the proposed HPSO-APO method is more efficient and robust than the standard PSO and APO methods in terms of getting diverse Pareto optimal solutions. Hence, the proposed hybrid method can be used for the large interconnected power system to solve MO-SCOPF problem with integration of wind and thermal generators.

  2. [Orthogonal experiments for optimizing the formulation and preparation conditions of temozolomide solid lipid nanoparticles].

    Dou, Mingjin; Huang, Guihua; Xi, Yanwei; Zhang, Na

    2008-10-01

    TMZ-SLN were prepared by emulsification-low temperature solidification method with stearic acid. The formulation and the preparation conditions were optimized by orthogonal experiments using entrapment efficiency as the evaluation index. The morphology was detected by transmission electron microscope. The Zeta potentials and the particle size distribution were evaluated by Laser Doppler Anemometry. The entrapment efficiencies and the drug release characteristics in vitro were assessed. The result showed that TMZ-SLN were concinnous and spherical in shape. The mean diameter (d(av) ) was 65.0 +/- 6.2 nm and the Zeta potential was -37.2 mV. The average entrapment efficiency was 58.9% +/- 1.21 %. The drug release behavior in vitro conformed to Higuchi Equation. The formation of a new material phase was testified by analysis of differential scanning calorimetry.

  3. Optimization of Gluten-Free Tulumba Dessert Formulation Including Corn Flour: Response Surface Methodology Approach

    Yildiz Önder

    2017-03-01

    Full Text Available Tulumba dessert is widely preferred in Turkey; however, it cannot be consumed by celiac patients because it includes gluten. The diversity of gluten-free products should be expanded so that celiac patients may meet their daily needs regularly. In this study, corn flour (CF / potato starch (PS blend to be used in the gluten-free tulumba dessert formulation was optimized using the Response Surface Methodology (RSM. Increasing ratio of PS in the CF-PS led to a decrease in hardness of the dessert and to an increase in expansion, viscosity, adhesiveness, yield of dessert both with and without syrup (P0.05, additionally these desserts had a much higher sensory score compared to the control sample in terms of the overall quality and pore structure (P<0.05.

  4. An optimized formulation of a thermostable spray dried virus-like particles vaccine against human papillomavirus

    Saboo, Sugandha; Tumban, Ebenezer; Peabody, Julianne; Wafula, Denis; Peabody, David S.; Chackerian, Bryce; Muttil, Pavan

    2016-01-01

    Existing vaccines against human papillomavirus (HPV) require continuous cold-chain storage. Previously, we developed a bacteriophage virus-like particle (VLP) based vaccine for Human Papillomavirus (HPV) infection, which elicits broadly neutralizing antibodies against diverse HPV types. Here, we formulated these VLPs into a thermostable dry powder using a multi-component excipient system and by optimizing the spray drying parameters using a half-factorial design approach. Dry powder VLPs were stable after spray drying and after long-term storage at elevated temperatures. Immunization of mice with a single dose of reconstituted dry powder VLPs that were stored at 37°C for more than a year elicited high anti-L2 IgG antibody titers. Spray dried thermostable, broadly protective L2 bacteriophage VLPs vaccine could be accessible to remote regions of the world (where ~84% of cervical cancer patients reside) by eliminating the cold-chain requirement during transportation and storage. PMID:27019231

  5. Experimental design approach to the process parameter optimization for laser welding of martensitic stainless steels in a constrained overlap configuration

    Khan, M. M. A.; Romoli, L.; Fiaschi, M.; Dini, G.; Sarri, F.

    2011-02-01

    This paper presents an experimental design approach to process parameter optimization for the laser welding of martensitic AISI 416 and AISI 440FSe stainless steels in a constrained overlap configuration in which outer shell was 0.55 mm thick. To determine the optimal laser-welding parameters, a set of mathematical models were developed relating welding parameters to each of the weld characteristics. These were validated both statistically and experimentally. The quality criteria set for the weld to determine optimal parameters were the minimization of weld width and the maximization of weld penetration depth, resistance length and shearing force. Laser power and welding speed in the range 855-930 W and 4.50-4.65 m/min, respectively, with a fiber diameter of 300 μm were identified as the optimal set of process parameters. However, the laser power and welding speed can be reduced to 800-840 W and increased to 4.75-5.37 m/min, respectively, to obtain stronger and better welds.

  6. Dynamic Optimization of Constrained Layer Damping Structure for the Headstock of Machine Tools with Modal Strain Energy Method

    Yakai Xu

    2017-01-01

    Full Text Available Dynamic stiffness and damping of the headstock, which is a critical component of precision horizontal machining center, are two main factors that influence machining accuracy and surface finish quality. Constrained Layer Damping (CLD structure is proved to be effective in raising damping capacity for the thin plate and shell structures. In this paper, one kind of high damping material is utilized on the headstock to improve damping capacity. The dynamic characteristic of the hybrid headstock is investigated analytically and experimentally. The results demonstrate that the resonant response amplitudes of the headstock with damping material can decrease significantly compared to original cast structure. To obtain the optimal configuration of damping material, a topology optimization method based on the Evolutionary Structural Optimization (ESO is implemented. Modal Strain Energy (MSE method is employed to analyze the damping and to derive the sensitivity of the modal loss factor. The optimization results indicate that the added weight of damping material decreases by 50%; meanwhile the first two orders of modal loss factor decrease by less than 23.5% compared to the original structure.

  7. Optimal control landscape for the generation of unitary transformations with constrained dynamics

    Hsieh, Michael; Wu, Rebing; Rabitz, Herschel; Lidar, Daniel

    2010-01-01

    The reliable and precise generation of quantum unitary transformations is essential for the realization of a number of fundamental objectives, such as quantum control and quantum information processing. Prior work has explored the optimal control problem of generating such unitary transformations as a surface-optimization problem over the quantum control landscape, defined as a metric for realizing a desired unitary transformation as a function of the control variables. It was found that under the assumption of nondissipative and controllable dynamics, the landscape topology is trap free, which implies that any reasonable optimization heuristic should be able to identify globally optimal solutions. The present work is a control landscape analysis, which incorporates specific constraints in the Hamiltonian that correspond to certain dynamical symmetries in the underlying physical system. It is found that the presence of such symmetries does not destroy the trap-free topology. These findings expand the class of quantum dynamical systems on which control problems are intrinsically amenable to a solution by optimal control.

  8. A globally nonsingular quaternion-based formulation for all-electric satellite trajectory optimization

    Libraro, Paola

    The general electric propulsion orbit-raising maneuver of a spacecraft must contend with four main limiting factors: the longer time of flight, multiple eclipses prohibiting continuous thrusting, long exposure to radiation from the Van Allen belt and high power requirement of the electric engines. In order to optimize a low-thrust transfer with respect to these challenges, the choice of coordinates and corresponding equations of motion used to describe the kinematical and dynamical behavior of the satellite is of critical importance. This choice can potentially affect the numerical optimization process as well as limit the set of mission scenarios that can be investigated. To increase the ability to determine the feasible set of mission scenarios able to address the challenges of an all-electric orbit-raising, a set of equations free of any singularities is required to consider a completely arbitrary injection orbit. For this purpose a new quaternion-based formulation of a spacecraft translational dynamics that is globally nonsingular has been developed. The minimum-time low-thrust problem has been solved using the new set of equations of motion inside a direct optimization scheme in order to investigate optimal low-thrust trajectories over the full range of injection orbit inclinations between 0 and 90 degrees with particular focus on high-inclinations. The numerical results consider a specific mission scenario in order to analyze three key aspects of the problem: the effect of the initial guess on the shape and duration of the transfer, the effect of Earth oblateness on transfer time and the role played by, radiation damage and power degradation in all-electric minimum-time transfers. Finally trade-offs between mass and cost savings are introduced through a test case.

  9. A method for stochastic constrained optimization using derivative-free surrogate pattern search and collocation

    Sankaran, Sethuraman; Audet, Charles; Marsden, Alison L.

    2010-01-01

    Recent advances in coupling novel optimization methods to large-scale computing problems have opened the door to tackling a diverse set of physically realistic engineering design problems. A large computational overhead is associated with computing the cost function for most practical problems involving complex physical phenomena. Such problems are also plagued with uncertainties in a diverse set of parameters. We present a novel stochastic derivative-free optimization approach for tackling such problems. Our method extends the previously developed surrogate management framework (SMF) to allow for uncertainties in both simulation parameters and design variables. The stochastic collocation scheme is employed for stochastic variables whereas Kriging based surrogate functions are employed for the cost function. This approach is tested on four numerical optimization problems and is shown to have significant improvement in efficiency over traditional Monte-Carlo schemes. Problems with multiple probabilistic constraints are also discussed.

  10. Design Optimization of Time- and Cost-Constrained Fault-Tolerant Distributed Embedded Systems

    Izosimov, Viacheslav; Pop, Paul; Eles, Petru

    2005-01-01

    In this paper we present an approach to the design optimization of fault-tolerant embedded systems for safety-critical applications. Processes are statically scheduled and communications are performed using the time-triggered protocol. We use process re-execution and replication for tolerating...... transient faults. Our design optimization approach decides the mapping of processes to processors and the assignment of fault-tolerant policies to processes such that transient faults are tolerated and the timing constraints of the application are satisfied. We present several heuristics which are able...

  11. Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function

    Pearson, John W.

    2012-11-21

    Optimal control problems with partial differential equations as constraints play an important role in many applications. The inclusion of bound constraints for the state variable poses a significant challenge for optimization methods. Our focus here is on the incorporation of the constraints via the Moreau-Yosida regularization technique. This method has been studied recently and has proven to be advantageous compared with other approaches. In this paper, we develop robust preconditioners for the efficient solution of the Newton steps associated with the fast solution of the Moreau-Yosida regularized problem. Numerical results illustrate the efficiency of our approach. © 2012 John Wiley & Sons, Ltd.

  12. An ensemble-based method for constrained reservoir life-cycle optimization

    Leeuwenburgh, O.; Egberts, P.J.P.; Chitu, A.G.

    2015-01-01

    We consider the problem of finding optimal long-term (life-cycle) recovery strategies for hydrocarbon reservoirs by use of simulation models. In such problems the presence of operating constraints, such as for example a maximum rate limit for a group of wells, may strongly influence the range of

  13. Constrained Optimization Problems in Cost and Managerial Accounting--Spreadsheet Tools

    Amlie, Thomas T.

    2009-01-01

    A common problem addressed in Managerial and Cost Accounting classes is that of selecting an optimal production mix given scarce resources. That is, if a firm produces a number of different products, and is faced with scarce resources (e.g., limitations on labor, materials, or machine time), what combination of products yields the greatest profit…

  14. Test Summary Report Vitrification Demonstration of an Optimized Hanford C-106/AY-102 Waste-Glass Formulation

    Goles, Ronald W.; Buchmiller, William C.; Hymas, Charles R.; MacIsaac, Brett D.

    2002-01-01

    In order to further the goal of optimizing Hanford?s HLW borosilicate flowsheet, a glass formulation effort was launched to develop an advanced high-capacity waste form exhibiting acceptable leach and crystal formation characteristics. A simulated C-106/AY-102 waste envelop inclusive of LAW pretreatment products was chosen as the subject of these nonradioactive optimization efforts. To evaluate this optimized borosilicate waste formulation under continuous dynamic vitrification conditions, a research-scale Joule-heated ceramic melter was used to demonstrate the advanced waste form?s flowsheet. The main objectives of this melter test was to evaluate (1) the processing characteristics of the newly formulated C-106/AY-102 surrogate melter-feed stream, (2) the effectiveness of sucrose as a glass-oxidation-state modifier, and (3) the impact of this reductant upon processing rates

  15. Application of mixture experimental design in the formulation and optimization of matrix tablets containing carbomer and hydroxy-propylmethylcellulose.

    Petrovic, Aleksandra; Cvetkovic, Nebojsa; Ibric, Svetlana; Trajkovic, Svetlana; Djuric, Zorica; Popadic, Dragica; Popovic, Radmila

    2009-12-01

    Using mixture experimental design, the effect of carbomer (Carbopol((R)) 971P NF) and hydroxypropylmethylcellulose (Methocel((R)) K100M or Methocel((R)) K4M) combination on the release profile and on the mechanism of drug liberation from matrix tablet was investigated. The numerical optimization procedure was also applied to establish and obtain formulation with desired drug release. The amount of TP released, release rate and mechanism varied with carbomer ratio in total matrix and HPMC viscosity. Increasing carbomer fractions led to a decrease in drug release. Anomalous diffusion was found in all matrices containing carbomer, while Case - II transport was predominant for tablet based on HPMC only. The predicted and obtained profiles for optimized formulations showed similarity. Those results indicate that Simplex Lattice Mixture experimental design and numerical optimization procedure can be applied during development to obtain sustained release matrix formulation with desired release profile.

  16. Formulating an optimal long-term energy supply strategy for Syria using MESSAGE model

    Hainoun, A.; Seif Aldin, M.; Almoustafa, S.

    2010-01-01

    An optimal long-term energy supply strategy has been formulated based on minimizing the total system costs for the entire study period 2003-2030. The national energy chain was modelled covering all energy levels and conversion technologies. The results indicate that the primary energy will grow at annual average rate of 4.8% arriving 68 Mtoe in 2030. The total installed electric capacity will be optimally expanded from 6885 to 19500 MW in 2030. Furthermore, to ensure supply security the future national energy system will rely mainly upon oil and natural gas (NG) with limited contribution of renewables and nuclear to the end of study period. The share of NG will increase gradually up to 2020 and then retreat. Owing to the continuous decrease of oil production, oil export is expected to vanish in 2012 and the country will import about 63% of its primary energy demand in 2030. Thus, the expected long-term development of national energy sector indicates a hard challenge for the future national economy. The employing of sensitivity analysis clarifies the importance of wind turbines operation time and discount rate. The analysis proves that nuclear option is insensitive to overnight cost increase up to 85% of the reference case value.

  17. Serum-free media formulations are cell line-specific and require optimization for microcarrier culture.

    Tan, Kah Yong; Teo, Kim Leng; Lim, Jessica F Y; Chen, Allen K L; Choolani, Mahesh; Reuveny, Shaul; Chan, Jerry; Oh, Steve Kw

    2015-08-01

    Mesenchymal stromal cells (MSCs) are being investigated as potential cell therapies for many different indications. Current methods of production rely on traditional monolayer culture on tissue-culture plastic, usually with the use of serum-supplemented growth media. However, the monolayer culturing system has scale-up limitations and may not meet the projected hundreds of billions to trillions batches of cells needed for therapy. Furthermore, serum-free medium offers several advantages over serum-supplemented medium, which may have supply and contaminant issues, leading to many serum-free medium formulations being developed. We cultured seven MSC lines in six different serum-free media and compared their growth between monolayer and microcarrier culture. We show that (i) expansion levels of MSCs in serum-free monolayer cultures may not correlate with expansion in serum-containing media; (ii) optimal culture conditions (serum-free media for monolayer or microcarrier culture) differ for each cell line; (iii) growth in static microcarrier culture does not correlate with growth in stirred spinner culture; (iv) and that early cell attachment and spreading onto microcarriers does not necessarily predict efficiency of cell expansion in agitated microcarrier culture. Current serum-free media developed for monolayer cultures of MSCs may not support MSC proliferation in microcarrier cultures. Further optimization in medium composition will be required for microcarrier suspension culture for each cell line. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  18. Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

    Dayong Zhou

    2008-12-01

    Full Text Available Tsatsanis and Xu have applied the constrained minimum output variance (CMOV principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

  19. Application of D-optimal experimental design method to optimize the formulation of O/W cosmetic emulsions.

    Djuris, J; Vasiljevic, D; Jokic, S; Ibric, S

    2014-02-01

    This study investigates the application of D-optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non-ionic emulsifier in the relatively low concentration (1%), and the mixture of co-emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations. To determine the optimal composition of co-emulsifiers mixture, D-optimal mixture experimental design was used. Prepared emulsions were characterized with rheological measurements, centrifugation test, specific conductivity and pH value measurements. All prepared samples appeared as white and homogenous creams, except for one homogenous and viscous lotion co-stabilized by stearic acid alone. Centrifugation testing revealed some phase separation only in the case of sample co-stabilized using glyceryl stearate alone. The obtained pH values indicated that all samples expressed mild acid value acceptable for cosmetic preparations. Specific conductivity values are attributed to the multiple phases O/W emulsions with high percentages of fixed water. Results of the rheological measurements have shown that the investigated samples exhibited non-Newtonian thixotropic behaviour. To determine the influence of each of the co-emulsifiers on emulsions properties, the obtained results were evaluated by the means of statistical analysis (ANOVA test). On the basis of comparison of statistical parameters for each of the studied responses, mixture reduced quadratic model was selected over the linear model implying that interactions between co-emulsifiers play the significant role in overall influence of co-emulsifiers on emulsions properties. Glyceryl stearate was found to be the dominant co-emulsifier affecting emulsions properties. Interactions between the glyceryl stearate and other co-emulsifiers were also found to significantly influence emulsions properties. These findings are especially important

  20. Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy

    Charles Tatkeu

    2008-12-01

    Full Text Available We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.

  1. Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy

    Zaouche, Abdelouahib; Dayoub, Iyad; Rouvaen, Jean Michel; Tatkeu, Charles

    2008-12-01

    We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR) strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA) are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.

  2. How does network design constrain optimal operation of intermittent water supply?

    Lieb, Anna; Wilkening, Jon; Rycroft, Chris

    2015-11-01

    Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.

  3. OPTIMIZATION OF CONTROL ACTIONS IN THE FORMULATION OF SAUSAGE PRODUCTS IN THE PRESENCE OF TECHNOLOGICAL DEFECTS

    A. V. Tokarev

    2015-01-01

    Full Text Available The problem of optimization of food additives in compounding of sausages for elimination of defects in meat raw materials at production management is considered in article. The mathematical problem definition and algorithm of its decision is offered. Formally the task is classified as a combinatory problem of integer linear programming which purpose is providing a set functional and technological and the taste of the final product at the minimum cost of unit of mass offood additives. The offered algorithm of the decision realizes a method of step-by-step creation of the decision with elimination of the unpromising options defined on the basis of recurrence relations. An example of determining the optimal set of food additives for the production of a particular case, when the recipe sausage "Stolichnaya" contains large amounts of fat-containing raw materials. To solve the problem of binding and emulsifying oily materials, as shown in the article are necessary supplements which together would contain: phosphate (pH regulator, water-retaining agent, antioxidant, emulsifier, thickener, gelling agent, animal protein (filler, coloring agent retainer color, flavor intensifier. For example, it was presented with a set of six different food additives with their technological and functional properties of flavor and cost. It was necessary to determine which of these to include in the food additives formulated so as to on the one hand they ultimately comprise a predetermined set of specified properties, and on the other - of the total cost was minimal. Solving this problem with the use of the considered algorithm was found the optimal set of food additives, which completely cover the set. This kit contains all the necessary ingredients for the task, and their total cost is minimal, unlike other possible combinations. The algorithm is realized in program system "MultiMeat Expert" in system of support of decision-making.

  4. [Development of an optimized formulation of damask marmalade with low energy level using Taguchi methodology].

    Villarroel, Mario; Castro, Ruth; Junod, Julio

    2003-06-01

    The goal of this present study was the development of an optimized formula of damask marmalade low in calories applying Taguchi methodology to improve the quality of this product. The selection of this methodology lies on the fact that in real life conditions the result of an experiment frequently depends on the influence of several variables, therefore, one expedite way to solve this problem is utilizing factorial desings. The influence of acid, thickener, sweetener and aroma additives, as well as time of cooking, and possible interactions among some of them, were studied trying to get the best combination of these factors to optimize the sensorial quality of an experimental formulation of dietetic damask marmalade. An orthogonal array L8 (2(7)) was applied in this experience, as well as level average analysis was carried out according Taguchi methodology to determine the suitable working levels of the design factors previously choiced, to achieve a desirable product quality. A sensory trained panel was utilized to analyze the marmalade samples using a composite scoring test with a descriptive acuantitative scale ranging from 1 = Bad, 5 = Good. It was demonstrated that the design factors sugar/aspartame, pectin and damask aroma had a significant effect (p < 0.05) on the sensory quality of the marmalade with 82% of contribution on the response. The optimal combination result to be: citric acid 0.2%; pectin 1%; 30 g sugar/16 mg aspartame/100 g, damask aroma 0.5 ml/100 g, time of cooking 5 minutes. Regarding chemical composition, the most important results turned out to be the decrease in carbohydrate content compaired with traditional marmalade with a reduction of 56% in coloric value and also the amount of dietary fiber greater than similar commercial products. Assays of storage stability were carried out on marmalade samples submitted to different temperatures held in plastic bags of different density. Non percetible sensorial, microbiological and chemical changes

  5. A preconditioner for optimal control problems, constrained by Stokes equation with a time-harmonic control

    Axelsson, Owe; Farouq, S.; Neytcheva, M.

    2017-01-01

    Roč. 310, January 2017 (2017), s. 5-18 ISSN 0377-0427 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : optimal control * time-harmonic Stokes problem * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www. science direct.com/ science /article/pii/S0377042716302631?via%3Dihub

  6. A preconditioner for optimal control problems, constrained by Stokes equation with a time-harmonic control

    Axelsson, Owe; Farouq, S.; Neytcheva, M.

    2017-01-01

    Roč. 310, January 2017 (2017), s. 5-18 ISSN 0377-0427 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : optimal control * time-harmonic Stokes problem * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www.sciencedirect.com/science/article/pii/S0377042716302631?via%3Dihub

  7. Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response

    Agosta, John Mark

    2013-01-01

    This paper works through the optimization of a real world planning problem, with a combination of a generative planning tool and an influence diagram solver. The problem is taken from an existing application in the domain of oil spill emergency response. The planning agent manages constraints that order sets of feasible equipment employment actions. This is mapped at an intermediate level of abstraction onto an influence diagram. In addition, the planner can apply a surveillance operator that...

  8. Stress-constrained truss topology optimization problems that can be solved by linear programming

    Stolpe, Mathias; Svanberg, Krister

    2004-01-01

    We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....

  9. Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems

    Guo, Weian; Li, Wuzhao; Zhang, Qun; Wang, Lei; Wu, Qidi; Ren, Hongliang

    2014-11-01

    In evolutionary algorithms, elites are crucial to maintain good features in solutions. However, too many elites can make the evolutionary process stagnate and cannot enhance the performance. This article employs particle swarm optimization (PSO) and biogeography-based optimization (BBO) to propose a hybrid algorithm termed biogeography-based particle swarm optimization (BPSO) which could make a large number of elites effective in searching optima. In this algorithm, the whole population is split into several subgroups; BBO is employed to search within each subgroup and PSO for the global search. Since not all the population is used in PSO, this structure overcomes the premature convergence in the original PSO. Time complexity analysis shows that the novel algorithm does not increase the time consumption. Fourteen numerical benchmarks and four engineering problems with constraints are used to test the BPSO. To better deal with constraints, a fuzzy strategy for the number of elites is investigated. The simulation results validate the feasibility and effectiveness of the proposed algorithm.

  10. Pricing and lot sizing optimization in a two-echelon supply chain with a constrained Logit demand function

    Yeison Díaz-Mateus

    2017-07-01

    Full Text Available Decision making in supply chains is influenced by demand variations, and hence sales, purchase orders and inventory levels are therefore concerned. This paper presents a non-linear optimization model for a two-echelon supply chain, for a unique product. In addition, the model includes the consumers’ maximum willingness to pay, taking socioeconomic differences into account. To do so, the constrained multinomial logit for discrete choices is used to estimate demand levels. Then, a metaheuristic approach based on particle swarm optimization is proposed to determine the optimal product sales price and inventory coordination variables. To validate the proposed model, a supply chain of a technological product was chosen and three scenarios are analyzed: discounts, demand segmentation and demand overestimation. Results are analyzed on the basis of profits, lotsizing and inventory turnover and market share. It can be concluded that the maximum willingness to pay must be taken into consideration, otherwise fictitious profits may mislead decision making, and although the market share would seem to improve, overall profits are not in fact necessarily better.

  11. An optimized probucol microencapsulated formulation integrating a secondary bile acid (deoxycholic acid as a permeation enhancer

    Mooranian A

    2014-09-01

    Full Text Available Armin Mooranian,1 Rebecca Negrulj,1 Nigel Chen-Tan,2 Gerald F Watts,3 Frank Arfuso,4 Hani Al-Salami11Biotechnology and Drug Development Research Laboratory, School of Pharmacy, Curtin Health Innovation Research Institute, Biosciences Research Precinct, Curtin University, 2Faculty of Science and Engineering, Curtin University, 3School of Medicine and Pharmacology, Royal Perth Hospital, University of Western Australia, 4School of Biomedical Science, Curtin Health Innovation Research Institute, Biosciences Research Precinct, Curtin University, Perth, AustraliaAbstract: The authors have previously designed, developed, and characterized a novel microencapsulated formulation as a platform for the targeted delivery of therapeutics in an animal model of type 2 diabetes, using the drug probucol (PB. The aim of this study was to optimize PB microcapsules by incorporating the bile acid deoxycholic acid (DCA, which has good permeation-enhancing properties, and to examine its effect on microcapsules’ morphology, rheology, structural and surface characteristics, and excipients’ chemical and thermal compatibilities. Microencapsulation was carried out using a BÜCHI-based microencapsulating system established in the authors’ laboratory. Using the polymer sodium alginate (SA, two microencapsulated formulations were prepared: PB-SA (control and PB-DCA-SA (test at a constant ratio (1:30 and 1:3:30, respectively. Complete characterization of the microcapsules was carried out. The incorporation of DCA resulted in better structural and surface characteristics, uniform morphology, and stable chemical and thermal profiles, while size and rheological parameters remained similar to control. In addition, PB-DCA-SA microcapsules showed good excipients’ compatibilities, which were supported by data from differential scanning calorimetry, Fourier transform infrared spectroscopy, scanning electron microscopy, and energy dispersive X-ray studies, suggesting

  12. Formulation and Optimization of Lansoprazole Pellets Using Factorial Design Prepared by Extrusion-Spheronization Technique Using Carboxymethyl Tamarind Kernel Powder.

    Muley, Sagar Sopanrao; Nandgude, Tanaji; Poddar, Sushilkumar

    2017-01-01

    In the present study, Lansoprazole pellets were prepared employing a novel excipient Carboxymethyl tamarind kernel powder (CMTKP) using extrusion-spheronization technique. Various research studies including patents have been carried out on this polymer. Pellet formulation was optimized for formulation parameters (concentration of microcrystalline cellulose, CMTKP, croscarmellose sodium and isopropyl alcohol). Process parameters (speed and duration of spheronization) were optimized using factorial design. The pellets were evaluated for yield, bulk and tapped density, particle size, hardness, drug content, disintegration time and drug release. The optimized batch showed 93.53% yield, 0.307 kg/cm2 hardness, 2.15 mm average particle size, 292 sec disintegration time and 90.46% drug content. Drug release of the optimized batch (2F7) and marketed formulation (LANZOL cap) was found to be 82.33% and 80.07%, respectively. An accelerated study indicated that optimized formulation was stable. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  13. WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

    Watkins, W.T.; Siebers, J.V. [University of Virginia, Charlottesville, VA (United States)

    2016-06-15

    Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

  14. WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

    Watkins, W.T.; Siebers, J.V.

    2016-01-01

    Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

  15. Optimization of a constrained linear monochromator design for neutral atom beams

    Kaltenbacher, Thomas

    2016-01-01

    A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1 μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100 nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up – a Fresnel zone plate in combination with a pinhole aperture – in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. - Highlights: • The presented results are essential for optimal operation conditions of a neutral atom microscope set-up. • The key parameters for the experimental arrangement of a neutral microscopy set-up are identified and their interplay is quantified. • Insights in the multidimensional problem provide deep and crucial understanding for pushing beyond the apparent focus limitations. • This work points out the trade-offs for high intensity and high spatial resolution indicating several use cases.

  16. Optimization of a constrained linear monochromator design for neutral atom beams

    Kaltenbacher, Thomas

    2016-04-15

    A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1 μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100 nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up – a Fresnel zone plate in combination with a pinhole aperture – in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. - Highlights: • The presented results are essential for optimal operation conditions of a neutral atom microscope set-up. • The key parameters for the experimental arrangement of a neutral microscopy set-up are identified and their interplay is quantified. • Insights in the multidimensional problem provide deep and crucial understanding for pushing beyond the apparent focus limitations. • This work points out the trade-offs for high intensity and high spatial resolution indicating several use cases.

  17. OPTIMIZATION OF DIRECT COMPRESSION TABLET FORMULATIONS FOR USE IN TROPICAL COUNTRIES

    Bos, C. E.; BOLHUIS, G. K.; LERK, C. F.; de Boer, J. H.; DUINEVELD, C. A. A.; Smilde, A. K.; Doornbos, D. A.

    1991-01-01

    With the aid of a combined mixture- and factorial- design, 2 standard tablet formulations were selected suitable for use in tropical countries. The formulations were based on native ingredients or ingredients that are available worldwide. The selection of the standard formulations was based on both

  18. A constrained tracking algorithm to optimize plug patterns in multiple isocenter Gamma Knife radiosurgery planning

    Li Kaile; Ma Lijun

    2005-01-01

    We developed a source blocking optimization algorithm for Gamma Knife radiosurgery, which is based on tracking individual source contributions to arbitrarily shaped target and critical structure volumes. A scalar objective function and a direct search algorithm were used to produce near real-time calculation results. The algorithm allows the user to set and vary the total number of plugs for each shot to limit the total beam-on time. We implemented and tested the algorithm for several multiple-isocenter Gamma Knife cases. It was found that the use of limited number of plugs significantly lowered the integral dose to the critical structures such as an optical chiasm in pituitary adenoma cases. The main effect of the source blocking is the faster dose falloff in the junction area between the target and the critical structure. In summary, we demonstrated a useful source-plugging algorithm for improving complex multi-isocenter Gamma Knife treatment planning cases

  19. Design Optimization of Mixed-Criticality Real-Time Applications on Cost-Constrained Partitioned Architectures

    Tamas-Selicean, Domitian; Pop, Paul

    2011-01-01

    In this paper we are interested to implement mixed-criticality hard real-time applications on a given heterogeneous distributed architecture. Applications have different criticality levels, captured by their Safety-Integrity Level (SIL), and are scheduled using static-cyclic scheduling. Mixed......-criticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Tasks...... slots on each processor and (iv) the schedule tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real...

  20. Adaptive near-optimal neuro controller for continuous-time nonaffine nonlinear systems with constrained input.

    Esfandiari, Kasra; Abdollahi, Farzaneh; Talebi, Heidar Ali

    2017-09-01

    In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Jacobi-Bellman (HJB) equation associated with the cost function is derived without requiring a priori knowledge about system dynamics. Weights of the identifier and critic NNs are tuned online and simultaneously such that unknown terms are approximated accurately and the control signal is kept between the saturation bounds. The convergence of NNs' weights, identification error, and system states is guaranteed using Lyapunov's direct method. Finally, simulation results are performed on two nonlinear systems to confirm the effectiveness of the proposed control strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Optimization of a constrained linear monochromator design for neutral atom beams.

    Kaltenbacher, Thomas

    2016-04-01

    A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up - a Fresnel zone plate in combination with a pinhole aperture - in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

    Liu, Qingshan; Wang, Jun

    2011-04-01

    This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

  3. Enhanced Solubility and Dissolution Rate of Lacidipine Nanosuspension: Formulation Via Antisolvent Sonoprecipitation Technique and Optimization Using Box-Behnken Design.

    Kassem, Mohamed A A; ElMeshad, Aliaa N; Fares, Ahmed R

    2017-05-01

    Lacidipine (LCDP) is a highly lipophilic calcium channel blocker of poor aqueous solubility leading to poor oral absorption. This study aims to prepare and optimize LCDP nanosuspensions using antisolvent sonoprecipitation technique to enhance the solubility and dissolution of LCDP. A three-factor, three-level Box-Behnken design was employed to optimize the formulation variables to obtain LCDP nanosuspension of small and uniform particle size. Formulation variables were as follows: stabilizer to drug ratio (A), sodium deoxycholate percentage (B), and sonication time (C). LCDP nanosuspensions were assessed for particle size, zeta potential, and polydispersity index. The formula with the highest desirability (0.969) was chosen as the optimized formula. The values of the formulation variables (A, B, and C) in the optimized nanosuspension were 1.5, 100%, and 8 min, respectively. Optimal LCDP nanosuspension had particle size (PS) of 273.21 nm, zeta potential (ZP) of -32.68 mV and polydispersity index (PDI) of 0.098. LCDP nanosuspension was characterized using x-ray powder diffraction, differential scanning calorimetry, and transmission electron microscopy. LCDP nanosuspension showed saturation solubility 70 times that of raw LCDP in addition to significantly enhanced dissolution rate due to particle size reduction and decreased crystallinity. These results suggest that the optimized LCDP nanosuspension could be promising to improve oral absorption of LCDP.

  4. Towards optimization of the silanization process of hydroxyapatite for its use in bone cement formulations

    Cisneros-Pineda, Olga G.; Herrera Kao, Wilberth; Loría-Bastarrachea, María I.; Veranes-Pantoja, Yaymarilis; Cauich-Rodríguez, Juan V.; Cervantes-Uc, José M.

    2014-01-01

    The aim of this work was to provide some fundamental information for optimization of silanization of hydroxyapatite intended for bone cement formulations. The effect of 3-(trimethoxysilyl) propyl methacrylate (MPS) concentration and solvent system (acetone/water or methanol/water mixtures) during HA silanization was monitored by X-ray diffraction (XRD), FTIR spectroscopy and EDX analysis. The effect of silanized HA on the mechanical properties of acrylic bone cements is also reported. It was found that the silanization process rendered hydroxyapatite with lower crystallinity compared to untreated HA. Through EDX, it was observed that the silicon concentration in the HA particles was higher for acetone–water than that obtained for methanol–water system, although the mechanical performance of cements prepared with these particles exhibited the opposite behavior. Taking all these results together, it is concluded that methanol–water system containing MPS at 3 wt.% provides the better results during silanization process of HA. - Highlights: • Effect of MPS concentration and solvents during HA silanization was studied. • Silanization rendered HA has lower crystallinity compared to untreated HA. • Silicon concentration was higher for acetone than that obtained using methanol. • Methanol–water system containing MPS at 3 wt.% provides the better results

  5. Sustained release biodegradable solid lipid microparticles: Formulation, evaluation and statistical optimization by response surface methodology

    Hanif Muhammad

    2017-12-01

    Full Text Available For preparing nebivolol loaded solid lipid microparticles (SLMs by the solvent evaporation microencapsulation process from carnauba wax and glyceryl monostearate, central composite design was used to study the impact of independent variables on yield (Y1, entrapment efficiency (Y2 and drug release (Y3. SLMs having a 10-40 μm size range, with good rheological behavior and spherical smooth surfaces, were produced. Fourier transform infrared spectroscopy, differential scanning calorimetry and X-ray diffractometry pointed to compatibility between formulation components and the zeta-potential study confirmed better stability due to the presence of negative charge (-20 to -40 mV. The obtained outcomes for Y1 (29-86 %, Y2 (45-83 % and Y3 (49-86 % were analyzed by polynomial equations and the suggested quadratic model were validated. Nebivolol release from SLMs at pH 1.2 and 6.8 was significantly (p 0.85 value (Korsmeyer- Peppas suggested slow erosion along with diffusion. The optimized SLMs have the potential to improve nebivolol oral bioavailability.

  6. Sustained release biodegradable solid lipid microparticles: Formulation, evaluation and statistical optimization by response surface methodology.

    Hanif, Muhammad; Khan, Hafeez Ullah; Afzal, Samina; Mahmood, Asif; Maheen, Safirah; Afzal, Khurram; Iqbal, Nabila; Andleeb, Mehwish; Abbas, Nazar

    2017-12-20

    For preparing nebivolol loaded solid lipid microparticles (SLMs) by the solvent evaporation microencapsulation process from carnauba wax and glyceryl monostearate, central composite design was used to study the impact of independent variables on yield (Y1), entrapment efficiency (Y2) and drug release (Y3). SLMs having a 10-40 μm size range, with good rheological behavior and spherical smooth surfaces, were produced. Fourier transform infrared spectroscopy, differential scanning calorimetry and X-ray diffractometry pointed to compatibility between formulation components and the zeta-potential study confirmed better stability due to the presence of negative charge (-20 to -40 mV). The obtained outcomes for Y1 (29-86 %), Y2 (45-83 %) and Y3 (49-86 %) were analyzed by polynomial equations and the suggested quadratic model were validated. Nebivolol release from SLMs at pH 1.2 and 6.8 was significantly (p 0.85 value (Korsmeyer- Peppas) suggested slow erosion along with diffusion. The optimized SLMs have the potential to improve nebivolol oral bioavailability.

  7. Shield Optimization and Formulation of Regression Equations for Split-Ring Resonator

    Tahir Ejaz

    2016-01-01

    Full Text Available Microwave resonators are widely used for numerous applications including communication, biomedical and chemical applications, material testing, and food grading. Split-ring resonators in both planar and nonplanar forms are a simple structure which has been in use for several decades. This type of resonator is characterized with low cost, ease of fabrication, moderate quality factor, low external noise interference, high stability, and so forth. Due to these attractive features and ease in handling, nonplanar form of structure has been utilized for material characterization in 1–5 GHz range. Resonant frequency and quality factor are two important parameters for determination of material properties utilizing perturbation theory. Shield made of conducting material is utilized to enclose split-ring resonator which enhances quality factor. This work presents a novel technique to develop shield around a predesigned nonplanar split-ring resonator to yield optimized quality factor. Based on this technique and statistical analysis regression equations have also been formulated for resonant frequency and quality factor which is a major outcome of this work. These equations quantify dependence of output parameters on various factors of shield made of different materials. Such analysis is instrumental in development of devices/designs where improved/optimum result is required.

  8. OPTIMIZATION OF DEMULSIFIER FORMULATION FOR SEPARATION OF WATER FROM CRUDE OIL EMULSIONS

    P. Hajivand

    2015-03-01

    Full Text Available Abstract In this study, various water-soluble and oil-soluble demulsifiers were selected for separation of water from crude oil emulsions and their productivity measured using the Bottle-test method at 70 °C and 10 ppm concentration. The best ones among 23 demulsifiers examined through the screening process were fatty alcohol ethoxylate, triethanol amine and urea from the water-soluble group and Basororol E2032, Basorol PDB 9935 and TOMAC from the oil-soluble category. Furthermore, the present study investigated the factors effective for demulsification such as temperature, concentration, pH, salinity and modifiers. It was found that the separation improves with increasing demulsifier concentration, increasing salt content, increasing temperature up to 80 °C, keeping the pH values between 5-9. Adding solvent modifiers proved unnecessary. Two formulations were prepared based on suggested optimal concentrations of demulsifier content by experimental design using Qualitec 4 and these proved to be highly effective in treating real and synthetic emulsions.

  9. OPTIMIZATION OF POTASSIUM NITRATE BASED SOLID PROPELLANT GRAINS FORMULATION USING RESPONSE SURFACE METHODOLOGY

    Oladipupo Olaosebikan Ogunleye

    2015-08-01

    Full Text Available This study was designed to evaluate the effect of propellant formulation and geometry on the solid propellant grains internal ballistic performance using core, bates, rod and tubular and end-burn geometries. Response Surface Methodology (RSM was used to analyze and optimize the effect of sucrose, potassium nitrate and carbon on the chamber pressure, temperature, thrust and specific impulse of the solid propellant grains through Central Composite Design (CCD of the experiment. An increase in potassium nitrate increased the specific impulse while an increase in sucrose and carbon decreased specific impulse. The coefficient of determination (R2 for models of chamber pressure, temperature, thrust and specific impulse in terms of composition and geometry were 0.9737, 0.9984, 0.9745 and 0.9589, respectively. The optimum specific impulse of 127.89 s, pressure (462201 Pa, temperature (1618.3 K and thrust (834.83 N were obtained using 0.584 kg of sucrose, 1.364 kg of potassium nitrate and 0.052 kg of carbon as well as bate geometry. There was no significant difference between the calculated and experimented ballistic properties at p < 0.05. The bate grain geometry is more efficient for minimizing the oscillatory pressure in the combustion chamber.

  10. Towards optimization of the silanization process of hydroxyapatite for its use in bone cement formulations

    Cisneros-Pineda, Olga G.; Herrera Kao, Wilberth; Loría-Bastarrachea, María I. [Centro de Investigación Científica de Yucatán, A.C., Unidad de Materiales, Calle 43 No. 130, Col. Chuburná de Hidalgo, C.P. 97200 Mérida, Yucatán (Mexico); Veranes-Pantoja, Yaymarilis [Centro de Biomateriales, Universidad de la Habana, Avenida Universidad, s/n, e/G y Ronda, C.P. 10600 C. de La Habana (Cuba); Cauich-Rodríguez, Juan V. [Centro de Investigación Científica de Yucatán, A.C., Unidad de Materiales, Calle 43 No. 130, Col. Chuburná de Hidalgo, C.P. 97200 Mérida, Yucatán (Mexico); Cervantes-Uc, José M., E-mail: manceruc@cicy.mx [Centro de Investigación Científica de Yucatán, A.C., Unidad de Materiales, Calle 43 No. 130, Col. Chuburná de Hidalgo, C.P. 97200 Mérida, Yucatán (Mexico)

    2014-07-01

    The aim of this work was to provide some fundamental information for optimization of silanization of hydroxyapatite intended for bone cement formulations. The effect of 3-(trimethoxysilyl) propyl methacrylate (MPS) concentration and solvent system (acetone/water or methanol/water mixtures) during HA silanization was monitored by X-ray diffraction (XRD), FTIR spectroscopy and EDX analysis. The effect of silanized HA on the mechanical properties of acrylic bone cements is also reported. It was found that the silanization process rendered hydroxyapatite with lower crystallinity compared to untreated HA. Through EDX, it was observed that the silicon concentration in the HA particles was higher for acetone–water than that obtained for methanol–water system, although the mechanical performance of cements prepared with these particles exhibited the opposite behavior. Taking all these results together, it is concluded that methanol–water system containing MPS at 3 wt.% provides the better results during silanization process of HA. - Highlights: • Effect of MPS concentration and solvents during HA silanization was studied. • Silanization rendered HA has lower crystallinity compared to untreated HA. • Silicon concentration was higher for acetone than that obtained using methanol. • Methanol–water system containing MPS at 3 wt.% provides the better results.

  11. Optimization of a High Temperature PEMFC micro-CHP System by Formulation and Application of a Process Integration Methodology

    Arsalis, Alexandros; Nielsen, Mads Pagh; Kær, Søren Knudsen

    2013-01-01

    A 1 kWe micro combined heat and power (CHP) system based on high temperature proton exchange membrane fuel cell (PEMFC) technology is modeled and optimized by formulation and application of a process integration methodology. The system can provide heat and electricity for a singlefamily household...

  12. Systematic Development of Transethosomal Gel System of Piroxicam: Formulation Optimization, In Vitro Evaluation, and Ex Vivo Assessment.

    Garg, Varun; Singh, Harmanpreet; Bhatia, Amit; Raza, Kaisar; Singh, Sachin Kumar; Singh, Bhupinder; Beg, Sarwar

    2017-01-01

    Piroxicam is used in the treatment of rheumatoid arthritis, osteoarthritis, and other inflammatory diseases. Upon oral administration, it is reported to cause ulcerative colitis, gastrointestinal irritation, edema and peptic ulcer. Hence, an alternative delivery system has been designed in the form of transethosome. The present study describes the preparation, optimization, characterization, and ex vivo study of piroxicam-loaded transethosomal gel using the central composite design. On the basis of the prescreening study, the concentration of lipids and ethanol was kept in the range of 2-4% w/v and 0-40% v/v, respectively. Formulation was optimized by measuring drug retention in the skin, drug permeation, entrapment efficiency, and vesicle size. Optimized formulation was incorporated in hydrogel and compared with other analogous vesicular (liposomes, ethosomes, and transfersomes) gels for the aforementioned responses. Among the various lipids used, soya phosphatidylcholine (SPL 70) and ethanol in various percentages were found to affect drug retention in the skin, drug permeation, vesicle size, and entrapment efficiency. The optimized batch of transethosome has shown 392.730 μg cm -2 drug retention in the skin, 44.312 μg cm -2  h -1 drug permeation, 68.434% entrapment efficiency, and 655.369 nm vesicle size, respectively. It was observed that the developed transethosomes were found superior in all the responses as compared to other vesicular formulations with improved stability and highest elasticity. Similar observations were noted with its gel formulation.

  13. 3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

    Jiekun Song

    2016-01-01

    Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

  14. Scheduling Multilevel Deadline-Constrained Scientific Workflows on Clouds Based on Cost Optimization

    Maciej Malawski

    2015-01-01

    Full Text Available This paper presents a cost optimization model for scheduling scientific workflows on IaaS clouds such as Amazon EC2 or RackSpace. We assume multiple IaaS clouds with heterogeneous virtual machine instances, with limited number of instances per cloud and hourly billing. Input and output data are stored on a cloud object store such as Amazon S3. Applications are scientific workflows modeled as DAGs as in the Pegasus Workflow Management System. We assume that tasks in the workflows are grouped into levels of identical tasks. Our model is specified using mathematical programming languages (AMPL and CMPL and allows us to minimize the cost of workflow execution under deadline constraints. We present results obtained using our model and the benchmark workflows representing real scientific applications in a variety of domains. The data used for evaluation come from the synthetic workflows and from general purpose cloud benchmarks, as well as from the data measured in our own experiments with Montage, an astronomical application, executed on Amazon EC2 cloud. We indicate how this model can be used for scenarios that require resource planning for scientific workflows and their ensembles.

  15. Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique.

    Karthivashan, Govindarajan; Masarudin, Mas Jaffri; Kura, Aminu Umar; Abas, Faridah; Fakurazi, Sharida

    2016-01-01

    This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as "flavonosome". Three widely established and therapeutically valuable flavonoids, such as quercetin (Q), kaempferol (K), and apigenin (A), were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA-phosphatidylcholine) through four different methods of synthesis - bulk (M1) and serialized (M2) co-sonication and bulk (M3) and sequential (M4) co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug-carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG). Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA-phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of -39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0.17%, 34.51%±2.07%, and 31.79%±0.01%, respectively. The in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics of the flavonoids indirectly depicts the release kinetic behavior of the flavonoids from the carrier. The QKA-loaded flavonosome had no indication of toxicity toward human hepatoma cell line as shown by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide result, wherein even at the higher concentration of 200 µg/mL, the flavonosomes exert >85% of cell viability. These results suggest that sequential loading technique may be a promising

  16. Multistage and multiobjective formulations of globally optimal upgradable expansions for electric power distribution systems

    Vaziri Yazdi Pin, Mohammad

    Electric power distribution systems are the last high voltage link in the chain of production, transport, and delivery of the electric energy, the fundamental goals of which are to supply the users' demand safely, reliably, and economically. The number circuit miles traversed by distribution feeders in the form of visible overhead or imbedded underground lines, far exceed those of all other bulk transport circuitry in the transmission system. Development and expansion of the distribution systems, similar to other systems, is directly proportional to the growth in demand and requires careful planning. While growth of electric demand has recently slowed through efforts in the area of energy management, the need for a continued expansion seems inevitable for the near future. Distribution system and expansions are also independent of current issues facing both the suppliers and the consumers of electrical energy. For example, deregulation, as an attempt to promote competition by giving more choices to the consumers, while it will impact the suppliers' planning strategies, it cannot limit the demand growth or the system expansion in the global sense. Curiously, despite presence of technological advancements and a 40-year history of contributions in the area, many of the major utilities still relay on experience and resort to rudimentary techniques when planning expansions. A comprehensive literature review of the contributions and careful analyses of the proposed algorithms for distribution expansion, confirmed that the problem is a complex, multistage and multiobjective problem for which a practical solution remains to be developed. In this research, based on the 15-year experience of a utility engineer, the practical expansion problem has been clearly defined and the existing deficiencies in the previous work identified and analyzed. The expansion problem has been formulated as a multistage planning problem in line with a natural course of development and industry

  17. Formulation, optimization, and pharmacodynamic evaluation of chitosan/phospholipid/β-cyclodextrin microspheres

    Shan L

    2016-01-01

    Full Text Available Lu Shan,1 En-Xue Tao,2 Qing-Hui Meng,3 Wen-Xia Hou,3 Kang Liu,1 Hong-Cai Shang,4 Jin-Bao Tang,1 Wei-Fen Zhang1,4 1School of Pharmacy, Weifang Medical University, 2The Affiliated Hospital of Weifang Medical University, 3School of Nursing, Weifang Medical University, Weifang, 4Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, People’s Republic of China Abstract: Cholinergic neurotransmission loss is the main cause of cognitive impairment in patients with Alzheimer’s disease. Phospholipids (PLs play an essential role in memory and learning abilities. Moreover, PLs act as a source of choline in acetylcholine synthesis. This study aimed to prepare and optimize the formulation of chitosan/phospholipid/β-cyclodextrin (CTS/PL/β-CD microspheres that can improve cognitive impairment. The CTS/PL/β-CD microspheres were prepared by spray drying, and optimized with an orthogonal design. These microspheres were also characterized in terms of morphology, structure, thermostability, drug loading, and encapsulation efficiency. The spatial learning and memory of rats were evaluated using the Morris water maze test, and the neuroprotective effects of the CTS/PL/β-CD microspheres were investigated by immunohistochemistry. Scanning electron microscopic images showed that the CTS/PL/β-CD microspheres were spherical with slightly wrinkled surfaces. Fourier transform infrared spectroscopy and differential scanning calorimetry proved that PLs formed hydrogen bonds with the amide group of CTS and the hydroxyl group of β-CD. The learning and memory abilities of rats in the treated group significantly improved compared with those in the model group. Immunohistochemical analysis revealed that treatment with the CTS/PL/β-CD microspheres attenuated the expression of protein kinase C-δ and inhibited the activation of microglias. These results suggest that the

  18. Benefits of Dairy Nutrients - Optimization of Formulations: The State of the Art in Moderate Acute Malnutrition

    Lagrange, Veronique; Dirienzo, Douglas

    2014-01-01

    Full text: Milk-derived ingredients provide important nutrients: high quality protein, minerals, B-vitamins, lactose, and bioactive factors for the treatment of moderate acute malnutrition (MAM). Milk proteins are high quality proteins due to their excellent digestibility, content of essential amino acids and branched chain amino acids, needed for growth. Lactose, a major component of human milk and dairy ingredients, can enhance palatability, provide energy and has been shown to enhance mineral absorption in infants. It may have beneficial effects on growth and enhance beneficial intestinal bacteria. Milk minerals can have effects on bone growth. These nutrients are available in variable proportions in milk and whey ingredients, allowing both nutritionists and food scientists to optimize (for cost effectiveness) formulations designed to treat and prevent MAM. Major options available to researchers are outlined. The use of RUTF in severe acute malnutrition (SAM) is now an established international standard of care. Studies have shown benefits in recovery rates when using RUTFs contain 25% milk when compared to 10% or no milk. In contrast to SAM, programs for the management of MAM had remained relatively unchanged over 30 years, with grain blends often provided. Recently, the addition of animal source foods has been recommended for promotion of growth in children with MAM, and testing of various formulations underway are highlighted. We review studies published since 2008 and assess the state of the science testing interventions that contain dairy ingredients for MAM. Clinical trials using new RUSF and CSB++ containing milk powder have demonstrated high recovery rates and benefits on growth. The identification of the optimal level of components of milk for treatment or prevention of MAM needs to be defined. Two studies currently testing levels of milk powders in supplements for MAM are in progress and will provide answers. One study is examining LNS with and without

  19. Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring

    Naixue Xiong

    2017-01-01

    Full Text Available Single-image blind deblurring for imaging sensors in the Internet of Things (IoT is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.

  20. Reliability analysis for cementless hip prosthesis using a new optimized formulation of yield stress against elasticity modulus relationship

    Kharmanda, G.

    2015-01-01

    Highlights: • We develop a new formulation between the yield stress and Young’s modulus of bone. • We validate the optimized formulation for cortical and trabecular bone. • We integrate the reliability analysis into artificially hip replacement design. - Abstract: Using classical design optimization methods for implant-bone studies does not completely guarantee a safety and satisfactory performance, due in part to the randomness of bone properties and loading. Here, the material properties of the different bone layers are considered as uncertain parameters. So their corresponding yield stress values will not be deterministic, that leads to integrate variable limitations into the optimization process. Here there is a strong need to find a reliable mathematical relationship between yield stress and material properties of the different bone layers. In this work, a new optimized formulation for yield stress against elasticity modulus relationship is first developed. This model is based on some experimental results. A validation of the proposed formulation is next carried out to show its accuracy for both bone layers (cortical and cancellous). A probabilistic sensitivity analysis is then carried out to show the role of each input parameter with respect to the limit state function. The new optimized formulation is next integrated into a reliability analysis problem in order to assess the reliability level of the stem–bone study where we deal with variable boundary limitations. An illustrative application is considered as a bi-dimensional example (contains only two variables) in order to present the results in an illustrative 2D space. Finally, a multi-variable problem considering several daily loading cases on a hip prosthesis shows the applicability of the proposed strategy

  1. PI controller design of a wind turbine: evaluation of the pole-placement method and tuning using constrained optimization

    Mirzaei, Mahmood; Tibaldi, Carlo; Hansen, Morten Hartvig

    2016-01-01

    to automatically tune the wind turbine controller subject to robustness constraints. The properties of the system such as the maximum sensitivity and complementary sensitivity functions (Ms and Mt), along with some of the responses of the system, are used to investigate the controller performance and formulate...... the optimization problem. The cost function is the integral absolute error (IAE) of the rotational speed from a disturbance modeled as a step in wind speed. Linearized model of the DTU 10-MW reference wind turbine is obtained using HAWCStab2. Thereafter, the model is reduced with model order reduction. The trade......PI/PID controllers are the most common wind turbine controllers. Normally a first tuning is obtained using methods such as pole-placement or Ziegler-Nichols and then extensive aeroelastic simulations are used to obtain the best tuning in terms of regulation of the outputs and reduction of the loads...

  2. Formulation development and optimization of Lamivudine 300 mg and Tenofovir Disoproxil Fumarate (TDF 300 mg FDC tablets by D-optimal mixture design

    Prosper Tibalinda

    2016-12-01

    Full Text Available The usage of fixed dose combination (FDC tablets of Lamivudine and Tenofovir Disoproxil Fumarate (TDF is increasing due to increased incidences of HIV/Hepatitis B and HIV/TB co-infections. This is likely to increase the financial crisis due to limited resources for funding procurement of ready-made products from the pharmaceuticals manufacturing leading countries. Therefore, production of local oral tablets containing Lamivudine and TDF FDC is inevitable. Lamivudine 300 mg/TDF 300 mg tablets were developed and optimized by D-optimal mixture design and produced by direct compression technique. Twenty trial formulations with independent variables, including PVP-CL 1–12.00%, PVP-K30 1–10.00%, starch-1500 2.5–12.5% and Avicel-PH102 2–19.25% were prepared by direct compression technique. The formulations were assessed on assay, dissolution, friability, weight variation and disintegration time. It was found that assay ranged from 98.13–101.95% for Lamivudine, 98.25–102.84 for TDF, both were within the in-house assay specification of 95 to 105%. Dissolution at single point was above 80% for Lamivudine 93.96–100.55% and 95.85–103.15% for TDF, disintegration time was between 1.92–66.33 min and friability 0.06–12.56%. Out of twenty formulation trials, eight formulations had all parameters in proven acceptable range. On optimization, one formulation with independent variables, PVP-CL 5.67%, PVP-K30 1.00%, Starch-1500 5.76% was selected. The optimized formulation was comparable to the reference product on the market with similarity factor (f2 and difference factor (f1 within the acceptable range for both Lamivudine and TDF.

  3. Assessment of electricity demand-supply in health facilities in resource-constrained settings : optimization and evaluation of energy systems for a case in Rwanda

    Palacios, S.G.

    2015-01-01

    In health facilities in resource-constrained settings, a lack of access to sustainable and reliable electricity can result on a sub-optimal delivery of healthcare services, as they do not have lighting for medical procedures and power to run essential equipment and devices to treat their patients.

  4. Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

    Regis, Rommel G.

    2014-02-01

    This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

  5. Tablet coating by injection molding technology - Optimization of coating formulation attributes and coating process parameters.

    Desai, Parind M; Puri, Vibha; Brancazio, David; Halkude, Bhakti S; Hartman, Jeremy E; Wahane, Aniket V; Martinez, Alexander R; Jensen, Keith D; Harinath, Eranda; Braatz, Richard D; Chun, Jung-Hoon; Trout, Bernhardt L

    2018-01-01

    We developed and evaluated a solvent-free injection molding (IM) coating technology that could be suitable for continuous manufacturing via incorporation with IM tableting. Coating formulations (coating polymers and plasticizers) were prepared using hot-melt extrusion and screened via stress-strain analysis employing a universal testing machine. Selected coating formulations were studied for their melt flow characteristics. Tablets were coated using a vertical injection molding unit. Process parameters like softening temperature, injection pressure, and cooling temperature played a very important role in IM coating processing. IM coating employing polyethylene oxide (PEO) based formulations required sufficient room humidity (>30% RH) to avoid immediate cracks, whereas other formulations were insensitive to the room humidity. Tested formulations based on Eudrajit E PO and Kollicoat IR had unsuitable mechanical properties. Three coating formulations based on hydroxypropyl pea starch, PEO 1,000,000 and Opadry had favorable mechanical (35% elongation, >95×10 4 J/m 3 toughness) and melt flow (>0.4g/min) characteristics, that rendered acceptable IM coats. These three formulations increased the dissolution time by 10, 15 and 35min, respectively (75% drug release), compared to the uncoated tablets (15min). Coated tablets stored in several environmental conditions remained stable to cracking for the evaluated 8-week time period. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique

    Karthivashan G

    2016-07-01

    Full Text Available Govindarajan Karthivashan,1 Mas Jaffri Masarudin,2 Aminu Umar Kura,1 Faridah Abas,3,4 Sharida Fakurazi1,5 1Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, 2Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, 3Department of Food Science, Faculty of Food Science and Technology, 4Laboratory of Natural Products, Institute of Bioscience, 5Department of Human Anatomy, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia Abstract: This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as “flavonosome”. Three widely established and therapeutically valuable flavonoids, such as quercetin (Q, kaempferol (K, and apigenin (A, were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA–phosphatidylcholine through four different methods of synthesis – bulk (M1 and serialized (M2 co-sonication and bulk (M3 and sequential (M4 co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug–carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG. Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA–phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of -39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0

  7. Formulation Optimization and Ex Vivo and In Vivo Evaluation of Celecoxib Microemulsion-Based Gel for Transdermal Delivery.

    Cao, Mengyuan; Ren, Lili; Chen, Guoguang

    2017-08-01

    Celecoxib (CXB) is a poorly aqueous solubility sulfonamide non-steroidal anti-inflammatory drug (NSAID). Hence, the formulation of CXB was selected for solubilization and bioavailability. To find out suitable formulation for microemulsion, the solubility of CXB in triacetin (oil phase), Tween 80 (surfactant), and Transcutol-P (co-surfactant) was screened respectively and optimized by using orthogonal experimental design. The Km value and concentration of oil, S mix , and water were confirmed by pseudo-ternary phase diagram studies and central composite design. One percent carbopol 934 was added to form CXB microemulsion-based gel. The final formulation was evaluated for its appearance, pH, viscosity, stability, drug content determination, globule size, and zeta potential. Its ex vivo drug permeation and the in vivo pharmacokinetic was investigated. Further research was performed to ensure the safety and validity by skin irritation study and in vivo anti-inflammatory activity study. Ex vivo permeation study in mice was designed to compare permeation and transdermal ability between microemulsion formulation and conventional gel. The results revealed that optimized microemulsion-based gel gained higher permeation based on smaller globule size and high drug loading of microemulsion. Transdermal ability was also greatly improved. Bioavailability was compared to market Celebrex® by the in vivo pharmacokinetic study in rabbits. The results indicated that CXB microemulsion-based gel had better bioavailability than Celebrex®.

  8. Formulation and optimization of chronomodulated press-coated tablet of carvedilol by Box–Behnken statistical design

    Satwara RS

    2012-08-01

    Full Text Available Rohan S Satwara, Parul K PatelDepartment of Pharmaceutics, Babaria Institute of Pharmacy, Vadodara, Gujarat, IndiaObjective: The primary objective of the present investigation was to formulate and optimize chronomodulated press-coated tablets to deliver the antihypertensive carvedilol at an effective quantity predawn, when a blood pressure spike is typically observed in most hypertensive patients.Experimental work: Preformulation studies and drug excipient compatibility studies were carried out for carvedilol and excipients. Core tablets (6 mm containing carvedilol and 10-mm press-coated tablets were prepared by direct compression. The Box–Behnken experimental design was applied to these press-coated tablets (F1–F15 formula with differing concentrations of rate-controlling polymers. Hydroxypropyl methyl cellulose K4M, ethyl cellulose, and K-carrageenan were used as rate-controlling polymers in the outer layer. These tablets were subjected to various precompression and postcompression tests. The optimized batch was derived both by statistically (using desirability function and graphically (using Design Expert® 8; Stat-Ease Inc. Tablets formulated using the optimized formulas were then evaluated for lag time and in vitro dissolution.Results and discussion: Results of preformulation studies were satisfactory. No interaction was observed between carvedilol and excipients by ultraviolet, Fourier transform infrared spectroscopy, and dynamic light scattering analysis. The results of precompression studies and postcompression studies were within limits. The varying lag time and percent cumulative carvedilol release after 8 h was optimized to obtain a formulation that offered a release profile with 6 h lag time, followed by complete carvedilol release after 8 h. The results showed no significant bias between predicted response and actual response for the optimized formula.Conclusion: Bedtime dosing of chronomodulated press-coated tablets may offer a

  9. A novel experimental design method to optimize hydrophilic matrix formulations with drug release profiles and mechanical properties.

    Choi, Du Hyung; Lim, Jun Yeul; Shin, Sangmun; Choi, Won Jun; Jeong, Seong Hoon; Lee, Sangkil

    2014-10-01

    To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

  10. Use of a continuous twin screw granulation and drying system during formulation development and process optimization.

    Vercruysse, J; Peeters, E; Fonteyne, M; Cappuyns, P; Delaet, U; Van Assche, I; De Beer, T; Remon, J P; Vervaet, C

    2015-01-01

    Since small scale is key for successful introduction of continuous techniques in the pharmaceutical industry to allow its use during formulation development and process optimization, it is essential to determine whether the product quality is similar when small quantities of materials are processed compared to the continuous processing of larger quantities. Therefore, the aim of this study was to investigate whether material processed in a single cell of the six-segmented fluid bed dryer of the ConsiGma™-25 system (a continuous twin screw granulation and drying system introduced by GEA Pharma Systems, Collette™, Wommelgem, Belgium) is predictive of granule and tablet quality during full-scale manufacturing when all drying cells are filled. Furthermore, the performance of the ConsiGma™-1 system (a mobile laboratory unit) was evaluated and compared to the ConsiGma™-25 system. A premix of two active ingredients, powdered cellulose, maize starch, pregelatinized starch and sodium starch glycolate was granulated with distilled water. After drying and milling (1000 μm, 800 rpm), granules were blended with magnesium stearate and compressed using a Modul™ P tablet press (tablet weight: 430 mg, main compression force: 12 kN). Single cell experiments using the ConsiGma™-25 system and ConsiGma™-1 system were performed in triplicate. Additionally, a 1h continuous run using the ConsiGma™-25 system was executed. Process outcomes (torque, barrel wall temperature, product temperature during drying) and granule (residual moisture content, particle size distribution, bulk and tapped density, hausner ratio, friability) as well as tablet (hardness, friability, disintegration time and dissolution) quality attributes were evaluated. By performing a 1h continuous run, it was detected that a stabilization period was needed for torque and barrel wall temperature due to initial layering of the screws and the screw chamber walls with material. Consequently, slightly deviating

  11. Crystallization Formulation Lab

    Federal Laboratory Consortium — The Crystallization Formulation Lab fills a critical need in the process development and optimization of current and new explosives and energetic formulations. The...

  12. Development of transethosomes formulation for dermal fisetin delivery: Box-Behnken design, optimization, in vitro skin penetration, vesicles-skin interaction and dermatokinetic studies.

    Moolakkadath, Thasleem; Aqil, Mohd; Ahad, Abdul; Imam, Syed Sarim; Iqbal, Babar; Sultana, Yasmin; Mujeeb, Mohd; Iqbal, Zeenat

    2018-05-07

    The present study was conducted for the optimization of transethosomes formulation for dermal fisetin delivery. The optimization of the formulation was carried out using "Box-Behnken design". The independent variables were Lipoid S 100, ethanol and sodium cholate. The prepared formulations were characterized for vesicle size, entrapment efficiency and in vitro skin penetration study. The vesicles-skin interaction, confocal laser scanning microscopy and dermatokinetic studies were performed with optimized formulation. Results of the present study demonstrated that the optimized formulation presented vesicle size of 74.21 ± 2.65 nm, zeta potential of -11.0 mV, entrapment efficiency of 68.31 ± 1.48% and flux of 4.13 ± 0.17 µg/cm 2 /h. The TEM image of optimized formulation exhibited sealed and spherical shape vesicles. Results of thermoanalytical techniques demonstrated that the prepared transethosomes vesicles formulation had fluidized the rigid membrane of rat's skin for smoother penetration of fisetin transethosomes. The confocal study results presented well distribution and penetration of Rhodamine B loaded transethosomes vesicles formulation up to deeper layers of the rat's skin as compared to the Rhodamine B-hydro alcoholic solution. Present study data revealed that the developed transethosomes vesicles formulation was found to be a potentially useful drug carrier for fisetin dermal delivery.

  13. Balancing emergency message dissemination and network lifetime in wireless body area network using ant colony optimization and Bayesian game formulation

    R. Latha

    Full Text Available Nowadays, Wireless Body Area Network (WBAN is emerging very fast and so many new methods and algorithms are coming up for finding the optimal path for disseminating emergency messages. Ant Colony Optimization (ACO is one of the cultural algorithms for solving many hard problems such as Travelling Salesman Problem (TSP. ACO is a natural behaviour of ants, which work stochastically with the help of pheromone trails deposited in the shortest route to find their food. This optimization procedure involves adapting, positive feedback and inherent parallelism. Each ant will deposit certain amount of pheromone in the tour construction it makes searching for food. This type of communication is known as stigmetric communication. In addition, if a dense WBAN environment prevails, such as hospital, i.e. in the environment of overlapping WBAN, game formulation was introduced for analyzing the mixed strategy behaviour of WBAN. In this paper, the ant colony optimization approach to the travelling salesman problem was applied to the WBAN to determine the shortest route for sending emergency message to the doctor via sensor nodes; and also a static Bayesian game formulation with mixed strategy was analysed to enhance the network lifetime. Whenever the patient needs any critical care or any other medical issue arises, emergency messages will be created by the WBAN and sent to the doctor's destination. All the modes of communication were realized in a simulation environment using OMNet++. The authors investigated a balanced model of emergency message dissemination and network lifetime in WBAN using ACO and Bayesian game formulation. Keywords: Wireless body area network, Ant colony optimization, Bayesian game model, Sensor network, Message latency, Network lifetime

  14. A new formulation of the equivalent thermal in optimization of hydrothermal systems

    Bayón L.

    2002-01-01

    Full Text Available In this paper, we revise the classical formulation of the problem depriving it of the concepts that are superfluous from the mathematical point of view. We observe that a number of power stations can be substituted by a single one that behaves equivalently to the entire set. Proceeding in this way, we obtain a variational formulation in its purest sense (without restrictions. This formulation allows us to employ the theory of calculus of variations to the highest degree. We then calculate the equivalent minimizer in the case where the cost functions are second-order polynomials. We prove that the equivalent minimizer is a second-order polynomial with piece-wise constant coefficients. Moreover, it belongs to the class C 1 . Finally, we present various examples prompted by real systems and perform the proposed algorithms using Mathematica.

  15. Disintegration mediated controlled release supersaturating solid dispersion formulation of an insoluble drug: design, development, optimization, and in vitro evaluation.

    Verma, Sanjay; Rudraraju, Varma S

    2015-02-01

    The objective of this study was to develop a solid dispersion based controlled release system for drug substances that are poorly soluble in water. A wax-based disintegration mediated controlled release system was designed based on the fact that an amorphous drug can crystallize out from hydrophilic matrices. For this study, cilostazol (CIL) was selected as the model drug, as it exhibits poor aqueous solubility. An amorphous solid dispersion was prepared to assist the drug to attain a supersaturated state. Povidone was used as carrier for solid dispersion (spray drying technique), hydrogenated vegetable oil (HVO) as wax matrix former, and sodium carboxymethyl cellulose (NaCMC) as a disintegrant. The extreme vertices mixture design (EVMD) was applied to optimize the designed and developed composition. The optimized formulation provided a dissolution pattern which was equivalent to the predicted curve, ascertaining that the optimal formulation could be accomplished with EVMD. The release profile of CIL was described by the Higuchi's model better than zero-order, first-order, and Hixson-Crowell's model, which indicated that the supersaturation state of CIL dominated to allow drug release by diffusion rather than disintegration regulated release as is generally observed by Hixson-Crowell's model. The optimized composition was evaluated for disintegration, dissolution, XRD, and stability studies. It was found that the amorphous state as well as the dissolution profile of CIL was maintained under the accelerated conditions of 40°C/75% RH for 6 months.

  16. Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

    Sundaramoorthi, Ganesh; Yezzi, Anthony

    2018-01-01

    We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

  17. Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

    Sundaramoorthi, Ganesh

    2018-04-04

    We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

  18. A targeted liposome delivery system for combretastatin A4: formulation optimization through drug loading and in vitro release studies.

    Nallamothu, Ramakrishna; Wood, George C; Kiani, Mohammad F; Moore, Bob M; Horton, Frank P; Thoma, Laura A

    2006-01-01

    Efficient liposomal therapeutics require high drug loading and low leakage. The objective of this study is to develop a targeted liposome delivery system for combretastatin A4 (CA4), a novel antivascular agent, with high loading and stable drug encapsulation. Liposomes composed of hydrogenated soybean phosphatidylcholine (HSPC), cholesterol, and distearoyl phosphoethanolamine-PEG-2000 conjugate (DSPE-PEG) were prepared by the lipid film hydration and extrusion process. Cyclic arginine-glycine-aspartic acid (RGD) peptides with affinity for alphav beta3-integrins overexpressed on tumor vascular endothelial cells were coupled to the distal end of polyethylene glycol (PEG) on the liposomes sterically stabilized with PEG (non-targeted liposomes; LCLs). Effect of lipid concentration, drug-to-lipid ratio, cholesterol, and DSPE-PEG content in the formulation on CA4 loading and its release from the liposomes was studied. Total liposomal CA4 levels obtained increased with increasing lipid concentration in the formulation. As the drug-to-lipid ratio increased from 10:100 to 20:100, total drug in the liposome formulation increased from 1.05+/-0.11 mg/mL to 1.55+/-0.13 mg/mL, respectively. When the drug-to-lipid ratio was further raised to 40:100, the total drug in liposome formulation did not increase, but the amount of free drug increased significantly, thereby decreasing the percent of entrapped drug. Increasing cholesterol content in the formulation decreased drug loading. In vitro drug leakage from the liposomes increased with increase in drug-to-lipid ratio or DSPE-PEG content in the formulation; whereas increasing cholesterol content of the formulation up to 30 mol-percent, decreased CA4 leakage from the liposomes. Ligand coupling to the liposome surface increased drug leakage as a function of ligand density. Optimized liposome formulation with 100 mM lipid concentration, 20:100 drug-to-lipid ratio, 30 mol-percent cholesterol, 4 mol-percent DSPE-PEG, and 1 mol

  19. Optimization of the formulation and technology of pearl millet based 'ready-to-reconstitute' kheer mix powder.

    Bunkar, Durga Shankar; Jha, Alok; Mahajan, Ankur

    2014-10-01

    The objective of this study was to optimize the process of manufacturing instant kheer mix based on pearl millet instead of rice. Dairy whitener, pearl millet and powdered sugar were the responses studied by employing the 3-factor Central Composite Rotatable Design. The formulation with 15 g sugar, 30 g dairy whitener and 20 g pearl millet was found suitable for obtaining dry kheer mix. The analyses were based on scores of consistency, cohesiveness, viscosity and overall acceptability. The reconstituted product from the formulated kheer mix had an overall acceptability score of 7.66 and desirability index of 0.7663. The moisture, fat, protein, carbohydrate and ash contents of the dry mix product were 2.8, 4.38, 5.84, 85.88 and 1.1 %, respectively.

  20. Optimization of edible coating formulations for improving postharvest quality and shelf life of pear fruit using response surface methodology.

    Nandane, A S; Dave, Rudri K; Rao, T V Ramana

    2017-01-01

    The effect of composite edible films containing soy protein isolate (SPI) in combination with additives like hydroxypropyl methylcellulose (HPMC) and olive oil on 'Babughosha' pear ( Pyrus communis L.) stored at ambient temperature (28 ± 5 °C and 60 ± 10% RH) was evaluated using Response surface methodology (RSM). A total of 30 edible coating formulations comprising of SPI (2-6%, w/v), olive oil (0.7-1.1%, v/v), HPMC (0.1-0.5%, w/v) and potassium sorbate (0-0.4% w/v) were evaluated for optimizing the most suitable combination. Quality parameters like weight loss%, TSS, pH and titrable acidity of the stored pears were selected as response variables for optimization. The optimization procedure was carried out using RSM. It was observed that the response variables were mainly effected by concentration of SPI and olive oil in the formulation. Edible coating comprising of SPI 5%, HPMC 0.40%, olive oil 1% and potassium sorbate 0.22% was found to be most suitable combination for pear fruit with predicted values of response variables indicated as weight loss% 3.50, pH 3.41, TSS 11.13 and TA% 0.513.

  1. Revisiting diesel fuel formulation from Petroleum light and middle refinery streams based on optimized engine behavior

    Ben Amara , Arij; Dauphin , Roland; Babiker , Hassan; Viollet , Yoann; Chang , Junseok; Jeuland , Nicolas; Amer , Amer

    2016-01-01

    International audience; The share of diesel fuel in European transport sector, which currently represents over 50% of total 11 demand, is increasing, requiring massive imports of this product, while at the same time, gasoline fuels are 12 today in surplus. In terms of air pollutant emissions, gasoline and kerosene streams have shown potential 13 in achieving lower emissions in Compression Ignition (CI) engines, particularly nitrogen oxides (NOx) 14 and particulates. A new fuel formulation app...

  2. IVABRADINE LOADED SOLID LIPID MICROPARTICLES: FORMULATION, CHARACTERIZATION AND OPTIMIZATION BY CENTRAL COMPOSITE ROTATABLE DESIGN.

    Hanif, Muhammad; Khan, Hafeez Ullah; Afzal, Samina; Sher, Muhammad

    2017-01-01

    The current research focused on improvement of oral bioavailability and decrease in dosing frequency of ivabradine (Iva) in order to enhance patient compliance by formulating novel sustained release Iva loaded solid lipid microparticles (SLMs) with the help of melt emulsification technique. SLMs formulations were designed with the help of three level central composite rotatable design (CCRD) to study the impact of independent variables like lipid concentration, surfactant concentration and stirring speed on responses - percentage yield (Y,) and entrapment efficiency (Y2). Compatibility between the drug and bees wax (BW) was checked by conducting Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and X-ray powder diffractometry (XRD). SLMs were further evaluated for rheological behavior, zeta potential, particle size and for morphology by scanning'electron microscope (SEM). The release of drug from SLMs was conducted by USP type-Il apparatus at pH 1.2, pH 6.8 and data were analyzed by different kinetic models like zero order, first order, Higuchi model, Korsmeyer-Peppas and Hixon-Crowell models. The rheo- logical studies approved the good flow behavior of SLMs and spherical smooth surface of SLMs was observed from SEM. DSC, FTIR and XRD studies concluded the lack of any possible interaction between formulation components. The size-of SLMs ranged from 300 to 500 pm and zeta potential study showed the presence of higher negative charge (-30 to -52 mV). Response Y, varied from 53 to 90% and response Y2 ranged from 29 to 78% indicating the effect of formulation variables. The obtained outcomes were analyzed by second order polynomial equation and suggested quadratic model was also validated. SLMs released Iva from 54 to 90% at pH 6.8 and was significantly (p 0.05) affected by BW concentration. The release mechanism followed the zero order and Korsmeyer-Peppas (n 0.85) kinetic models suggesting slow erosion along with diffusion

  3. Field-based optimal-design of an electric motor: a new sensitivity formulation

    Barba, Paolo Di; Mognaschi, Maria Evelina; Lowther, David Alister; Wiak, Sławomir

    2017-12-01

    In this paper, a new approach to robust optimal design is proposed. The idea is to consider the sensitivity by means of two auxiliary criteria A and D, related to the magnitude and isotropy of the sensitivity, respectively. The optimal design of a switched-reluctance motor is considered as a case study: since the case study exhibits two design criteria, the relevant Pareto front is approximated by means of evolutionary computing.

  4. On the formulation and numerical simulation of distributed-order fractional optimal control problems

    Zaky, M. A.; Machado, J. A. Tenreiro

    2017-11-01

    In a fractional optimal control problem, the integer order derivative is replaced by a fractional order derivative. The fractional derivative embeds implicitly the time delays in an optimal control process. The order of the fractional derivative can be distributed over the unit interval, to capture delays of distinct sources. The purpose of this paper is twofold. Firstly, we derive the generalized necessary conditions for optimal control problems with dynamics described by ordinary distributed-order fractional differential equations (DFDEs). Secondly, we propose an efficient numerical scheme for solving an unconstrained convex distributed optimal control problem governed by the DFDE. We convert the problem under consideration into an optimal control problem governed by a system of DFDEs, using the pseudo-spectral method and the Jacobi-Gauss-Lobatto (J-G-L) integration formula. Next, we present the numerical solutions for a class of optimal control problems of systems governed by DFDEs. The convergence of the proposed method is graphically analyzed showing that the proposed scheme is a good tool for the simulation of distributed control problems governed by DFDEs.

  5. The Use of D-Optimal Mixture Design in Optimising Okara Soap Formulation for Stratum Corneum Application

    Borhan, Farrah Payyadhah; Abd Gani, Siti Salwa; Shamsuddin, Rosnah

    2014-01-01

    Okara, soybean waste from tofu and soymilk production, was utilised as a natural antioxidant in soap formulation for stratum corneum application. D-optimal mixture design was employed to investigate the influence of the main compositions of okara soap containing different fatty acid and oils (virgin coconut oil A (24–28% w/w), olive oil B (15–20% w/w), palm oil C (6–10% w/w), castor oil D (15–20% w/w), cocoa butter E (6–10% w/w), and okara F (2–7% w/w)) by saponification process on the response hardness of the soap. The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for okara soap hardness in terms of the six design factors considered in this study. Results revealed that the best mixture was the formulation that included 26.537% A, 19.999% B, 9.998% C, 16.241% D, 7.633% E, and 7.000% F. The results proved that the difference in the level of fatty acid and oils in the formulation significantly affects the hardness of soap. Depending on the desirable level of those six variables, creation of okara based soap with desirable properties better than those of commercial ones is possible. PMID:25548777

  6. The Use of D-Optimal Mixture Design in Optimising Okara Soap Formulation for Stratum Corneum Application

    Farrah Payyadhah Borhan

    2014-01-01

    Full Text Available Okara, soybean waste from tofu and soymilk production, was utilised as a natural antioxidant in soap formulation for stratum corneum application. D-optimal mixture design was employed to investigate the influence of the main compositions of okara soap containing different fatty acid and oils (virgin coconut oil A (24–28% w/w, olive oil B (15–20% w/w, palm oil C (6–10% w/w, castor oil D (15–20% w/w, cocoa butter E (6–10% w/w, and okara F (2–7% w/w by saponification process on the response hardness of the soap. The experimental data were utilized to carry out analysis of variance (ANOVA and to develop a polynomial regression model for okara soap hardness in terms of the six design factors considered in this study. Results revealed that the best mixture was the formulation that included 26.537% A, 19.999% B, 9.998% C, 16.241% D, 7.633% E, and 7.000% F. The results proved that the difference in the level of fatty acid and oils in the formulation significantly affects the hardness of soap. Depending on the desirable level of those six variables, creation of okara based soap with desirable properties better than those of commercial ones is possible.

  7. The use of D-optimal mixture design in optimising okara soap formulation for stratum corneum application.

    Borhan, Farrah Payyadhah; Abd Gani, Siti Salwa; Shamsuddin, Rosnah

    2014-01-01

    Okara, soybean waste from tofu and soymilk production, was utilised as a natural antioxidant in soap formulation for stratum corneum application. D-optimal mixture design was employed to investigate the influence of the main compositions of okara soap containing different fatty acid and oils (virgin coconut oil A (24-28% w/w), olive oil B (15-20% w/w), palm oil C (6-10% w/w), castor oil D (15-20% w/w), cocoa butter E (6-10% w/w), and okara F (2-7% w/w)) by saponification process on the response hardness of the soap. The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for okara soap hardness in terms of the six design factors considered in this study. Results revealed that the best mixture was the formulation that included 26.537% A, 19.999% B, 9.998% C, 16.241% D, 7.633% E, and 7.000% F. The results proved that the difference in the level of fatty acid and oils in the formulation significantly affects the hardness of soap. Depending on the desirable level of those six variables, creation of okara based soap with desirable properties better than those of commercial ones is possible.

  8. Sufficient Descent Polak-Ribière-Polyak Conjugate Gradient Algorithm for Large-Scale Box-Constrained Optimization

    Qiuyu Wang

    2014-01-01

    descent method at first finite number of steps and then by conjugate gradient method subsequently. Under some appropriate conditions, we show that the algorithm converges globally. Numerical experiments and comparisons by using some box-constrained problems from CUTEr library are reported. Numerical comparisons illustrate that the proposed method is promising and competitive with the well-known method—L-BFGS-B.

  9. Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles

    Ajinath Eknath Shirsat

    2015-01-01

    Full Text Available The purpose of present study was to optimize rizatriptan (RZT chitosan (CS nanoparticles using ionic gelation method by application of quality by design (QbD approach. Based on risk assessment, effect of three variables, that is CS %, tripolyphosphate % and stirring speed were studied on critical quality attributes (CQAs; particle size and entrapment efficiency. Central composite design (CCD was implemented for design of experimentation with 20 runs. RZT CS nanoparticles were characterized for particle size, polydispersity index, entrapment efficiency, in-vitro release study, differential scanning calorimetric, X-ray diffraction, scanning electron microscopy (SEM. Based on QbD approach, design space (DS was optimized with a combination of selected variables with entrapment efficiency > 50% w/w and a particle size between 400 and 600 nm. Validation of model was performed with 3 representative formulations from DS for which standard error of − 0.70-3.29 was observed between experimental and predicted values. In-vitro drug release followed initial burst release 20.26 ± 2.34% in 3-4 h with sustained drug release of 98.43 ± 2.45% in 60 h. Lower magnitude of standard error for CQAs confirms the validation of selected CCD model for optimization of RZT CS nanoparticles. In-vitro drug release followed dual mechanism via, diffusion and polymer erosion. RZT CS nanoparticles were prepared successfully using QbD approach with the understanding of the high risk process and formulation parameters involved and optimized DS with a multifactorial combination of critical parameters to obtain predetermined RZT loaded CS nanoparticle specifications.

  10. Optimization of a novel improver gel formulation for Barbari flat bread using response surface methodology.

    Pourfarzad, Amir; Haddad Khodaparast, Mohammad Hossein; Karimi, Mehdi; Mortazavi, Seyed Ali

    2014-10-01

    Nowadays, the use of bread improvers has become an essential part of improving the production methods and quality of bakery products. In the present study, the Response Surface Methodology (RSM) was used to determine the optimum improver gel formulation which gave the best quality, shelf life, sensory and image properties for Barbari flat bread. Sodium stearoyl-2-lactylate (SSL), diacetyl tartaric acid esters of monoglyceride (DATEM) and propylene glycol (PG) were constituents of the gel and considered in this study. A second-order polynomial model was fitted to each response and the regression coefficients were determined using least square method. The optimum gel formulation was found to be 0.49 % of SSL, 0.36 % of DATEM and 0.5 % of PG when desirability function method was applied. There was a good agreement between the experimental data and their predicted counterparts. Results showed that the RSM, image processing and texture analysis are useful tools to investigate, approximate and predict a large number of bread properties.

  11. Optimization of the Formulation of Prebiotic Milk Chocolate Based on Rheological Properties

    Hannaneh Farzanmehr

    2009-01-01

    Full Text Available Rheological properties are very important parameters in the production of products with high-quality and desirable texture. So far, many attempts to produce low-calorie milk chocolate have not succeeded. Therefore, the present study aims to evaluate the effects of sugar substitutes on rheological characteristics of prebiotic milk chocolate using Simplex-lattice mixture design. For doing this, a prebiotic compound (inulin with two bulking agents (polydextrose and maltodextrin at different levels (0–100 % along with sucralose were used. Fifteen formulations covering the entire range of a triangular simplex were examined in order to find the optimum levels. All chocolates showed thixotropic and shear thinning behaviour and among the evaluated mathematical models, Casson model showed the best fitting for predicting rheological properties. According to our findings, chocolate formulations containing high levels of sugar substitutes (where a single component predominated had higher moisture content, Casson viscosity and yield stress than others, including the control. In contrast, the lowest moisture content, Casson viscosity and yield stress were observed at medium levels. Therefore, the optimum values for substitution of sucrose and production of a low-calorie prebiotic milk chocolate are 8–28 % and 67–86 % for inulin, 0–19 % and 31–69 % for polydextrose and 0–47 % for maltodextrin, respectively.

  12. Optimization of conditions for probiotic curd formulation by Enterococcus faecium MTCC 5695 with probiotic properties using response surface methodology.

    Ramakrishnan, Vrinda; Goveas, Louella Concepta; Prakash, Maya; Halami, Prakash M; Narayan, Bhaskar

    2014-11-01

    Enterococcus faecium MTCC 5695 possessing potential probiotic properties as well as enterocin producing ability was used as starter culture. Effect of time (12-24 h) and inoculum level (3-7 % v/v) on cell growth, bacteriocin production, antioxidant property, titrable acidity and pH of curd was studied by response surface methodology (RSM). The optimized conditions were 26.48 h and 2.17%v/v inoculum and the second order model validated. Co cultivation studies revealed that the formulated product had the ability to prevent growth of foodborne pathogens that affect keeping quality of the product during storage. The results indicated that application of E. faecium MTCC 5695 along with usage of optimized conditions attributed to the formation of highly consistent well set curd with bioactive and bioprotective properties. Formulated curd with potential probiotic attributes can be used as therapeutic agent for the treatment of foodborne diseases like Traveler's diarrhea and gastroenteritis which thereby help in improvement of bowel health.

  13. Improved solution for ill-posed linear systems using a constrained optimization ruled by a penalty: evaluation in nuclear medicine tomography

    Walrand, Stephan; Jamar, François; Pauwels, Stanislas

    2009-01-01

    Ill-posed linear systems occur in many different fields. A class of regularization methods, called constrained optimization, aims to determine the extremum of a penalty function whilst constraining an objective function to a likely value. We propose here a novel heuristic way to screen the local extrema satisfying the discrepancy principle. A modified version of the Landweber algorithm is used for the iteration process. After finding a local extremum, a bound is performed to the 'farthest' estimate in the data space still satisfying the discrepancy principle. Afterwards, the modified Landweber algorithm is again applied to find a new local extremum. This bound-iteration process is repeated until a satisfying solution is reached. For evaluation in nuclear medicine tomography, a novel penalty function that preserves the edge steps in the reconstructed solution was evaluated on Monte Carlo simulations and using real SPECT acquisitions as well. Surprisingly, the first bound always provided a significantly better solution in a wide range of statistics

  14. Optimization of the production process of hybrid and multivalent formulation Bombesin/RGD for the opportune detection of breast cancer

    Robles M, M.

    2013-01-01

    The radiopharmaceuticals of third generation are used in nuclear medicine to obtain images of specific molecular targets, and they are unique in their capacity to detect in vivo specific biochemical sites as receptors that are over-expressed in diverse illness. In cancer cells several types of receptors are over-expressed, as the integrin s α(v)β(3) and α(v)β(5) that specifically recognize the sequence RGD (Arginine-Glycin-Ac. Aspartic) and gastrin-releasing peptide that recognizes specifically to the peptide Lys 3 -Bombesin. The integrin s α(v)β(3) and α(v)β(5) are involved in the tumor angio genesis processes and the gastrin-releasing peptide is over-expressed in breast and prostate cancer. The molecular recognition of the specific receptors is the basis to be utilized as targets of the radiopharmaceuticals 99m Tc-HYNIC-Bombesin and 99m Tc-HYNIC-RGD. In this work was developed a lyophilized pharmaceutical formulation effective, stable and safe for the simultaneous obtaining of the radiopharmaceuticals 99m Tc-HYNIC-Bombesin ( 99m Tc-EDDA/HYNIC-Lys 3 -Bombesin) and 99m Tc-HYNIC-RGD ( 99m Tc EDDA/HYNIC-E-[c(RGDfK)] 2 ). Later on the production process of the product HYNIC-Bombesin/RGD-Sn was optimized using a factorial design and the formulation was transferred to the production plant of radiopharmaceuticals of the Instituto Nacional de Investigaciones Nucleares (ININ). The optimized formulation is described in the following chart: HYNIC-[Lys 3 ]-Bombesin - 12.5 μg; HYNIC-E-c[RGDfK] 2 - 12.5 μg; Stannous chloride (SnCl 2 ) - 20 μg; Ethylenediamine diacetic acid (EDDA) - 10 mg; N-tris(hydroxymethyl)methyl glycin (Tricine) - 20 mg; Mannitol - 50 mg. The production process was validated and were carried out the stability studies under refrigeration conditions. (Author)

  15. MILP formulation for the optimal operation of the integrated gas and power system

    Fang, Jiakun; Chen, Zhe; Ai, Xiaomeng

    2017-01-01

    -to-gas technology is also modeled together with gas-fired generators to enable bi directional energy conversion between the gas and power systems. The major advance of the proposed model is that the linepack storage in every pipe can be assessed and optimally utilized. Simulation results show the unit commitment...

  16. Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

    Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

    2011-04-04

    A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Formulation optimization of transdermal meloxicam potassium-loaded mesomorphic phases containing ethanol, oleic acid and mixture surfactant using the statistical experimental design methodology.

    Huang, Chi-Te; Tsai, Chia-Hsun; Tsou, Hsin-Yeh; Huang, Yaw-Bin; Tsai, Yi-Hung; Wu, Pao-Chu

    2011-01-01

    Response surface methodology (RSM) was used to develop and optimize the mesomorphic phase formulation for a meloxicam transdermal dosage form. A mixture design was applied to prepare formulations which consisted of three independent variables including oleic acid (X(1)), distilled water (X(2)) and ethanol (X(3)). The flux and lag time (LT) were selected as dependent variables. The result showed that using mesomorphic phases as vehicles can significantly increase flux and shorten LT of drug. The analysis of variance showed that the permeation parameters of meloxicam from formulations were significantly influenced by the independent variables and their interactions. The X(3) (ethanol) had the greatest potential influence on the flux and LT, followed by X(1) and X(2). A new formulation was prepared according to the independent levels provided by RSM. The observed responses were in close agreement with the predicted values, demonstrating that RSM could be successfully used to optimize mesomorphic phase formulations.

  18. Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco

    Kerschke, Pascal

    2017-01-01

    Choosing the best-performing optimizer(s) out of a portfolio of optimization algorithms is usually a difficult and complex task. It gets even worse, if the underlying functions are unknown, i.e., so-called Black-Box problems, and function evaluations are considered to be expensive. In the case of continuous single-objective optimization problems, Exploratory Landscape Analysis (ELA) - a sophisticated and effective approach for characterizing the landscapes of such problems by means of numeric...

  19. Second-Order Necessary Optimality Conditions for Some State-Constrained Control Problems of Semilinear Elliptic Equations

    Casas, E.; Troeltzsch, F.

    1999-01-01

    In this paper we are concerned with some optimal control problems governed by semilinear elliptic equations. The case of a boundary control is studied. We consider pointwise constraints on the control and a finite number of equality and inequality constraints on the state. The goal is to derive first- and second-order optimality conditions satisfied by locally optimal solutions of the problem

  20. Vitamin E TPGS emulsified vinorelbine bitartrate loaded solid lipid nanoparticles (SLN): Formulation development, optimization and in vitro characterization.

    Maurya, Lakshmi; Rajamanickam, Vijayakumar Mahalingam; Narayan, Gopeshwar; Singh, Sanjay

    2018-04-08

    Vinorelbine bitartrate (VRL), a semi synthetic vinca alkaloid approved for breast cancer, has been proved to beneficial as first line and subsequent therapies. However, it's hydrophilic and thermo labile nature provides hindrance to oral clinical translation. The current work focused on the application of DOE a modern statistical optimization tool for the development and optimization of a solid lipid nanoparticle (SLN) formulation that can encapsulate hydrophilic and thermolabile Vinorelbine bitartrate (VRL) to a maximum extent without compromising integrity and anticancer activity of the drug. SLNs were prepared by solvent diffusion technique employing Taguchi orthogonal array design with optimized formulation and process variables. The emulsifying nature and low melting point of glyceryl mono-oleate (GMO) were exploited to enhance entrapment and minimizing temperature associated degradation, respectively. Moreover, two types of surfactants, Vitamin E TPGS (TPGS) and Poloxamer-188 were utilized to obtain TPGS-VRL-SLNs and PL-VRL-SLNs, respectively. The SLNs were characterized for various physicochemical properties, in-vitro drug release kinetics and anticancer activity by MTT assay on MCF-7 cancer cell lines. The SLNs were found to be spherical in shape with entrapment efficiency (EE) up to 58 %. In-vitro release studies showed biphasic release pattern following Korsemeyer peppas model with fickian release kinetics. Results of MTT assay revealed that TPGS-VRL-SLNs and PL-VRL-SLNs were 39.5 and 18.5 fold more effective, respectively, compared to the pristine VRL. DOE approach was successfully applied for the development of VRL-SLNs. Enhanced entrapment and anticancer efficacy of TPGS-VRL-SLN can be attributed to emulsifying nature of GMO and inherent cytotoxic nature of TPGS, respectively, which synergizes with VRL. Therefore, TPGS associated SLNs may be potential carrier in cancer chemotherapeutics. Copyright© Bentham Science Publishers; For any queries, please

  1. Formulation and Application of Optimal Homotopty Asymptotic Method to Coupled Differential - Difference Equations

    Ullah, Hakeem; Islam, Saeed; Khan, Ilyas; Shafie, Sharidan; Fiza, Mehreen

    2015-01-01

    In this paper we applied a new analytic approximate technique Optimal Homotopy Asymptotic Method (OHAM) for treatment of coupled differential- difference equations (DDEs). To see the efficiency and reliability of the method, we consider Relativistic Toda coupled nonlinear differential-difference equation. It provides us a convenient way to control the convergence of approximate solutions when it is compared with other methods of solution found in the literature. The obtained solutions show that OHAM is effective, simpler, easier and explicit. PMID:25874457

  2. Factor analysis in optimization of formulation of high content uniformity tablets containing low dose active substance

    Lukášová, I.; Muselík, J.; Franc, A.; Goněc, R.; Mika, Filip; Vetchý, D.

    2017-01-01

    Roč. 109, NOV (2017), s. 541-547 ISSN 0928-0987 R&D Projects: GA MŠk(CZ) LO1212; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : factor analysis * process optimization * sampling error * worst case Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering OBOR OECD: Medical laboratory technology (including laboratory samples analysis Impact factor: 3.756, year: 2016

  3. Formulation and application of optimal homotopty asymptotic method to coupled differential-difference equations.

    Ullah, Hakeem; Islam, Saeed; Khan, Ilyas; Shafie, Sharidan; Fiza, Mehreen

    2015-01-01

    In this paper we applied a new analytic approximate technique Optimal Homotopy Asymptotic Method (OHAM) for treatment of coupled differential-difference equations (DDEs). To see the efficiency and reliability of the method, we consider Relativistic Toda coupled nonlinear differential-difference equation. It provides us a convenient way to control the convergence of approximate solutions when it is compared with other methods of solution found in the literature. The obtained solutions show that OHAM is effective, simpler, easier and explicit.

  4. A nodally condensed SUPG formulation for free-surface computation of steady-state flows constrained by unilateral contact - Application to rolling

    Arora, Shitij; Fourment, Lionel

    2018-05-01

    In the context of the simulation of industrial hot forming processes, the resultant time-dependent thermo-mechanical multi-field problem (v →,p ,σ ,ɛ ) can be sped up by 10-50 times using the steady-state methods while compared to the conventional incremental methods. Though the steady-state techniques have been used in the past, but only on simple configurations and with structured meshes, and the modern-days problems are in the framework of complex configurations, unstructured meshes and parallel computing. These methods remove time dependency from the equations, but introduce an additional unknown into the problem: the steady-state shape. This steady-state shape x → can be computed as a geometric correction t → on the domain X → by solving the weak form of the steady-state equation v →.n →(t →)=0 using a Streamline Upwind Petrov Galerkin (SUPG) formulation. There exists a strong coupling between the domain shape and the material flow, hence, a two-step fixed point iterative resolution algorithm was proposed that involves (1) the computation of flow field from the resolution of thermo-mechanical equations on a prescribed domain shape and (2) the computation of steady-state shape for an assumed velocity field. The contact equations are introduced in the penalty form both during the flow computation as well as during the free-surface correction. The fact that the contact description is inhomogeneous, i.e., it is defined in the nodal form in the former, and in the weighted residual form in the latter, is assumed to be critical to the convergence of certain problems. Thus, the notion of nodal collocation is invoked in the weak form of the surface correction equation to homogenize the contact coupling. The surface correction algorithm is tested on certain analytical test cases and the contact coupling is tested with some hot rolling problems.

  5. Optimization of a sponge cake formulation with inulin as fat replacer: structure, physicochemical, and sensory properties.

    Rodríguez-García, Julia; Puig, Ana; Salvador, Ana; Hernando, Isabel

    2012-02-01

    The effects of several fat replacement levels (0%, 35%, 50%, 70%, and 100%) by inulin in sponge cake microstructure and physicochemical properties were studied. Oil substitution for inulin decreased significantly (P cake structure development during baking. Cryo-SEM micrographs of cake crumbs showed a continuous matrix with embedded starch granules and coated with oil; when fat replacement levels increased, starch granules appeared as detached structures. Cakes with fat replacement up to 70% had a high crumb air cell values; they were softer and rated as acceptable by an untrained sensory panel (n = 51). So, the reformulation of a standard sponge cake recipe to obtain a new product with additional health benefits and accepted by consumers is achieved. Practical Application:  In this study, fat is replaced by inulin in cakes, which is a fiber mainly obtained from chicory roots. Sponge cake formulations with reductions in fat content up to 70% are achieved. These high-quality products can be labeled as "reduced in fat" according to U.S. FDA (2009) and EU regulations (European-Union 2006). © 2012 Institute of Food Technologists®

  6. Optimization and Validation of Quantitative Spectrophotometric Methods for the Determination of Alfuzosin in Pharmaceutical Formulations

    M. Vamsi Krishna

    2007-01-01

    Full Text Available Three accurate, simple and precise spectrophotometric methods for the determination of alfuzosin hydrochloride in bulk drugs and tablets are developed. The first method is based on the reaction of alfuzosin with ninhydrin reagent in N, N'-dimethylformamide medium (DMF producing a colored product which absorbs maximally at 575 nm. Beer’s law is obeyed in the concentration range 12.5-62.5 µg/mL of alfuzosin. The second method is based on the reaction of drug with ascorbic acid in DMF medium resulting in the formation of a colored product, which absorbs maximally at 530 nm. Beer’s law is obeyed in the concentration 10-50 µg/mL of alfuzosin. The third method is based on the reaction of alfuzosin with p-benzoquinone (PBQ to form a colored product with λmax at 400 nm. The products of the reaction were stable for 2 h at room temperature. The optimum experimental parameters for the reactions have been studied. The validity of the described procedures was assessed. Statistical analysis of the results has been carried out revealing high accuracy and good precision. The proposed methods could be used for the determination of alfuzosin in pharmaceutical formulations. The procedures were rapid, simple and suitable for quality control application.

  7. Formulation analysis and computation of an optimization-based local-to-nonlocal coupling method.

    D' Elia, Marta [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research; Bochev, Pavel Blagoveston [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research

    2017-01-01

    In this paper, we present an optimization-based coupling method for local and nonlocal continuum models. Our approach couches the coupling of the models into a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the local and nonlocal problem domains, and the virtual controls are the nonlocal volume constraint and the local boundary condition. We present the method in the context of Local-to-Nonlocal di usion coupling. Numerical examples illustrate the theoretical properties of the approach.

  8. Optimization of energy and water use in multipurpose batch plants using an improved mathematical formulation

    Seid, ER

    2014-05-01

    Full Text Available and its as- sociated thermal storage policy for recircu- lated hot/cold heat storage medium (HEN). Most of the previous works solved this se- quentially. Foo et al. (2008) extended the minimum units targeting and network evo- lution techniques that were...) reviewed these techniques based on graphical-based pinch analysis and mathematical optimization approach. The seminal work on pinch analysis application to batch water network was reported by Wang and Smith (1994). Foo et al. (2005) proposed a time...

  9. SU-E-T-574: Novel Chance-Constrained Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

    An, Y; Liang, J; Liu, W

    2015-01-01

    Purpose: We propose to apply a probabilistic framework, namely chanceconstrained optimization, in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to hedge against the influence of uncertainties and improve robustness of treatment plans. Methods: IMPT plans were generated for a typical prostate patient. Nine dose distributions are computed — the nominal one and one each for ±5mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. These nine dose distributions are supplied to the solver CPLEX as chance constraints to explicitly control plan robustness under these representative uncertainty scenarios with certain probability. This probability is determined by the tolerance level. We make the chance-constrained model tractable by converting it to a mixed integer optimization problem. The quality of plans derived from this method is evaluated using dose-volume histogram (DVH) indices such as tumor dose homogeneity (D5% – D95%) and coverage (D95%) and normal tissue sparing like V70 of rectum, V65, and V40 of bladder. We also compare the results from this novel method with the conventional PTV-based method to further demonstrate its effectiveness Results: Our model can yield clinically acceptable plans within 50 seconds. The chance-constrained optimization produces IMPT plans with comparable target coverage, better target dose homogeneity, and better normal tissue sparing compared to the PTV-based optimization [D95% CTV: 67.9 vs 68.7 (Gy), D5% – D95% CTV: 11.9 vs 18 (Gy), V70 rectum: 0.0 % vs 0.33%, V65 bladder: 2.17% vs 9.33%, V40 bladder: 8.83% vs 21.83%]. It also simultaneously makes the plan more robust [Width of DVH band at D50%: 2.0 vs 10.0 (Gy)]. The tolerance level may be varied to control the tradeoff between plan robustness and quality. Conclusion: The chance-constrained optimization generates superior IMPT plan compared to the PTV-based optimization with

  10. Optimization of formulation of soy-cakes baked in infrared-microwave combination oven by response surface methodology.

    Şakıyan, Özge

    2015-05-01

    The aim of present work is to optimize the formulation of a functional cake (soy-cake) to be baked in infrared-microwave combination oven. For this optimization process response surface methodology was utilized. It was also aimed to optimize the processing conditions of the combination baking. The independent variables were the baking time (8, 9, 10 min), the soy flour concentration (30, 40, 50 %) and the DATEM (diacetyltartaric acid esters of monoglycerides) concentration (0.4, 0.6 and 0.8 %). The quality parameters that were examined in the study were specific volume, weight loss, total color change and firmness of the cake samples. The results were analyzed by multiple regression; and the significant linear, quadratic, and interaction terms were used in the second order mathematical model. The optimum baking time, soy-flour concentration and DATEM concentration were found as 9.5 min, 30 and 0.72 %, respectively. The corresponding responses of the optimum points were almost comparable with those of conventionally baked soy-cakes. So it may be declared that it is possible to produce high quality soy cakes in a very short time by using infrared-microwave combination oven.

  11. Formulation Development, Optimization, and In vitro - In vivo Characterization of Natamycin Loaded PEGylated Nano-lipid Carriers for Ocular Applications.

    Patil, Akash; Lakhani, Prit; Taskar, Pranjal; Wu, Kai-Wei; Sweeney, Corinne; Avula, Bharathi; Wang, Yan-Hong; Khan, Ikhlas A; Majumdar, Soumyajit

    2018-04-23

    Current study aimed at formulating and optimizing natamycin (NT) loaded PEGylated NLCs (NT-PEG-NLCs) using Box-Behnken Design and investigating their potential in ocular applications. Response surface methodology (RSM) computations and plots for optimization were performed using Design Expert ® software, to obtain optimum values for response variables based on the criteria of desirability. Optimized NT-PEG-NLCs had predicted values for the dependent variables not significantly different from the experimental values. NT-PEG-NLCs were characterized for their physicochemical parameters; NT's rate of permeation and flux across rabbit cornea was evaluated, in vitro; ocular tissue distribution was assessed in rabbits, in vivo. NT-PEG-NLCs were found to have optimum particle size (< 300 nm) narrow PDI, high NT entrapment and NT content. In vitro transcorneal permeability and flux of NT from NT-PEG-NLCs was significantly higher than Natacyn ® . NT-PEG-NLC (0.3%) showed improved delivery of NT across the intact cornea and provided concentrations statistically similar to the marketed suspension (5%) in inner ocular tissues, in vivo, indicating that it could be a potential alternative to the conventional suspension during the course of fungal keratitis therapy. Copyright © 2018. Published by Elsevier Inc.

  12. Formulation, optimization and characterization of cationic polymeric nanoparticles of mast cell stabilizing agent using the Box-Behnken experimental design.

    Gajra, Balaram; Patel, Ravi R; Dalwadi, Chintan

    2016-01-01

    The present research work was intended to develop and optimize sustained release of biodegradable chitosan nanoparticles (CSNPs) as delivery vehicle for sodium cromoglicate (SCG) using the circumscribed Box-Behnken experimental design (BBD) and evaluate its potential for oral permeability enhancement. The 3-factor, 3-level BBD was employed to investigate the combined influence of formulation variables on particle size and entrapment efficiency (%EE) of SCG-CSNPs prepared by ionic gelation method. The generated polynomial equation was validated and desirability function was utilized for optimization. Optimized SCG-CSNPs were evaluated for physicochemical, morphological, in-vitro characterizations and permeability enhancement potential by ex-vivo and uptake study using CLSM. SCG-CSNPs exhibited particle size of 200.4 ± 4.06 nm and %EE of 62.68 ± 2.4% with unimodal size distribution having cationic, spherical, smooth surface. Physicochemical and in-vitro characterization revealed existence of SCG in amorphous form inside CSNPs without interaction and showed sustained release profile. Ex-vivo and uptake study showed the permeability enhancement potential of CSNPs. The developed SCG-CSNPs can be considered as promising delivery strategy with respect to improved permeability and sustained drug release, proving importance of CSNPs as potential oral delivery system for treatment of allergic rhinitis. Hence, further studies should be performed for establishing the pharmacokinetic potential of the CSNPs.

  13. OPTIMIZATION AND VALIDATION OF HPLC METHOD FOR TETRAMETHRIN DETERMINATION IN HUMAN SHAMPOO FORMULATION.

    Zeric Stosic, Marina Z; Jaksic, Sandra M; Stojanov, Igor M; Apic, Jelena B; Ratajac, Radomir D

    2016-11-01

    High-performance liquid chromatography (HPLC) method with diode array detection (DAD) were optimized and validated for separation and determination of tetramethrin in an antiparasitic human shampoo. In order to optimize separation conditions, two different columns, different column oven temperatures, as well as mobile phase composition and ratio, were tested. Best separation was achieved on the Supelcosil TM LC-18- DB column (4.6 x 250 mm), particle size 5 jim, with mobile phase methanol : water (78 : 22, v/v) at a flow rate of 0.8 mL/min and at temperature of 30⁰C. The detection wavelength of the detector was set at 220 nm. Under the optimum chromatographic conditions, standard calibration curve was measured with good linearity [r2 = 0.9997]. Accuracy of the method defined as a mean recovery of tetramethrin from shampoo matrix was 100.09%. The advantages of this method are that it can easily be used for the routine analysis of drug tetramethrin in pharmaceutical formulas and in all pharmaceutical researches involving tetramethrin.

  14. Formulation design and optimization of novel fast dissolving tablet of chlorpheniramine maleate by using lyophilization techniques

    Vivek Dave

    2017-06-01

    Full Text Available Fast dissolving tablets (FDTs have received more interest in the pharmaceutical industry for those categories of drug which show slow dissolution and less oral bioavailability. Nowadays various technologies have been developed for FDTs with improved patient compliance and convenience. FDTs tablets provide an advantage particularly for the pediatric and geriatric patients who have difficulty in swallowing and also for that who are travelling for a long and suffers from lack of water availability. Lyophilization (freeze-drying is a process in which water is sublimated from the product after freezing at a specific temperature and pressure. Lyophilization technique is used in order to improve the dissolution of the given substance and improve the oral bioavailability of the drugs with poor solubility and high permeability. In this work, chlorpheniramine maleate FDTs was formulated by lyophilization method. The prepared tablets were subjected to various evaluation such as hardness (2.4–2.9 kg/cm2, friability (0.68–0.79%, disintegration time (10–19 s, drug content (95.32–99.09%, water absorption ratio (31–53%, wetting time (64–106 s and in-vitro drug release shown in 5 min (96.04–99.92%. FTIR studies showed that there is no interaction between drug and polymer. Stability studies showed that there is no change in drug content within three and six months. Results revealed that fast dissolving tablets of chlorpheniramine maleate prepared by lyophilization method result in rapid dissolution.

  15. Nanoemulsion-based gel formulation of diclofenac diethylamine: design, optimization, rheological behavior and in vitro diffusion studies.

    Hamed, Rania; Basil, Marwa; AlBaraghthi, Tamadur; Sunoqrot, Suhair; Tarawneh, Ola

    2016-12-01

    Chronic oral administration of the non-steroidal anti-inflammatory drug, diclofenac diethylamine (DDEA), is often associated with gastrointestinal ulcers and bleeding. As an alternative to oral administration, a nanoemulsion-based gel (NE gel) formulation of DDEA was developed for topical administration. An optimized formulation for the o/w nanoemulsion of oil, surfactant and cosurfactant was selected based on nanoemulsion mean droplet size, clarity, stability, and flowability, and incorporated into the gelling agent Carbopol® 971P. Rheological studies of the DDEA NE gel were conducted and compared to those of conventional DDEA gel and emulgel. The three gels exhibited an elastic behavior, where G' dominated G″ at all frequencies, indicating the formation of strong gels. NE gel exhibited higher G' values than conventional gel and emulgel, which indicated the formation of a stronger gel network. Strat-M® membrane, a synthetic membrane with diffusion characteristics that are well correlated to human skin, was used for the in vitro diffusion studies. The release of DDEA from conventional gel, emulgel and NE gel showed a controlled release pattern over 12 h, which was consistent with the rheological properties of the gels. DDEA release kinetics from the three gels followed super case II transport as fitted by Korsmeyer-Peppas model.

  16. Optimization of fat-reduced ice cream formulation employing inulin as fat replacer via response surface methodology.

    Pintor, Aurora; Severiano-Pérez, Patricia; Totosaus, Alfonso

    2014-10-01

    The use of new ingredients like inulin for fat replacement is of wide application in the food industry. The aim of the present work was to reduce the fat content on ice cream formulations. It was possible to reduce up to 25% of butyric and vegetable fats with 3% of inulin, with good textural and sensory characteristics of the final product. The substitution of fat with inulin increased the ice cream mix viscosity, improved air incorporation, and produced ice cream with soft and homogeneous textures. Color characteristics were not affected by the replacement. Hedonic sensory analysis showed that optimized fat-reduced inulin ice cream was not perceived different to commercial vanilla ice cream. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  17. How to stabilize cilazapril-containing solid dosage forms? The optimization of a final drug formulation

    Katarzyna Regulska

    2017-03-01

    Full Text Available Cilazapril, a moisture-sensitive compound, is known to undergo rapid degradation which could be additionally facilitated by the presence of excipients that contain or absorb moisture. Hence we investigated the stability of cilazapril in two commercially-available dosage forms and in binary mixtures with the selected excipients used in the studied commercial formulations i.e.: hypromellose, lactose monohydrate, maize starch and talc in order to detect any possible, stability-affecting incompatibilities. Also the impact of the blister made of oriented polyamide/aluminum/polyvinyl chloride//aluminum on cilazapril-containing tablets was researched. A validated HPLC and HPLC-MS methods were used for analysis and the isothermal stress testing conditions were applied (temperature range 318–343 K, relative humidity 76.4% for tablets and temperature 333 K, relative humidity range 50.9–76.4% for binary mixtures. It was shown that the degradation of cilazapril in both, model mixtures and tablets follows the autocatalytic model kinetics and it is more rapid than that observed for pure substance, evidenced by higher degradation rate constants. The immediate packaging protects cilazapril in tablets from degradation only in case of the original drug while in its blistered generic counterpart a slight but statistically insignificant increase of cilazapril decay occurs when compared to bare tablets (p < 0.05. The degradation product of cilazapril in tablets and binary mixtures was identified as cilazaprilat. It was also observed that the increase of relative humidity or the presence of hypromellose, lactose and talc significantly impairs the stability of cilazapril in the aforementioned order. Only maize starch exhibited a positive effect on cilazapril stability (10.8% loss of cilazapril in binary mixture after 360 days of stressing compared to 35% loss of pure cilazapril in analogous test conditions probably thanks to its moisture-scavenging properties

  18. Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

    Baofeng Cai

    2017-08-01

    Full Text Available The Interconnected River System Network Project (IRSNP is a significant water supply engineering project, which is capable of effectively utilizing flood resources to generate ecological value, by connecting 198 lakes and ponds in western Jilin, northeast China. In this article, an optimization research approach has been proposed to maximize the incremental value of IRSNP ecosystem services. A double-sided chance-constrained integer linear program (DCCILP method has been proposed to support the optimization, which can deal with uncertainties presented as integers or random parameters that appear on both sides of the decision variable at the same time. The optimal scheme indicates that after rational optimization, the total incremental value of ecosystem services from the interconnected river system network project increased 22.25%, providing an increase in benefits of 3.26 × 109 ¥ compared to the original scheme. Most of the functional area is swamp wetland, which provides the greatest ecological benefits. Adjustment services increased obviously, implying that the optimization scheme prioritizes ecological benefits rather than supply and production services.

  19. Factor analysis in optimization of formulation of high content uniformity tablets containing low dose active substance.

    Lukášová, Ivana; Muselík, Jan; Franc, Aleš; Goněc, Roman; Mika, Filip; Vetchý, David

    2017-11-15

    Warfarin is intensively discussed drug with narrow therapeutic range. There have been cases of bleeding attributed to varying content or altered quality of the active substance. Factor analysis is useful for finding suitable technological parameters leading to high content uniformity of tablets containing low amount of active substance. The composition of tabletting blend and technological procedure were set with respect to factor analysis of previously published results. The correctness of set parameters was checked by manufacturing and evaluation of tablets containing 1-10mg of warfarin sodium. The robustness of suggested technology was checked by using "worst case scenario" and statistical evaluation of European Pharmacopoeia (EP) content uniformity limits with respect to Bergum division and process capability index (Cpk). To evaluate the quality of active substance and tablets, dissolution method was developed (water; EP apparatus II; 25rpm), allowing for statistical comparison of dissolution profiles. Obtained results prove the suitability of factor analysis to optimize the composition with respect to batches manufactured previously and thus the use of metaanalysis under industrial conditions is feasible. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Optimization of corn, rice and buckwheat formulations for gluten-free wafer production.

    Dogan, Ismail Sait; Yildiz, Onder; Meral, Raciye

    2016-07-01

    Gluten-free baked products for celiac sufferers are essential for healthy living. Cereals having gluten such as wheat and rye must be removed from the diet for the clinical and histological improvement. The variety of gluten-free foods should be offered for the sufferers. In the study, gluten-free wafer formulas were optimized using corn, rice and buckwheat flours, xanthan and guar gum blend as an alternative product for celiac sufferers. Wafer sheet attributes and textural properties were investigated. Considering all wafer sheet properties in gluten-free formulas, better results were obtained by using 163.5% water, 0.5% guar and 0.1% xanthan in corn formula; 173.3% water, 0.45% guar and 0.15% xanthan gum in rice formula; 176% water, 0.1% guar and 0.5% xanthan gum in buckwheat formula. Average desirability values in gluten-free formulas were between 0.86 and 0.91 indicating they had similar visual and textural profiles to control sheet made with wheat flour. © The Author(s) 2015.

  1. Formulation and optimization of mucoadhesive buccal patches of losartan potassium by using response surface methodology

    Ikram, Md.; Gilhotra, Neeraj; Gilhotra, Ritu Mehra

    2015-01-01

    Background: This study was undertaken with an aim to systematically design a model of factors that would yield an optimized sustained release dosage form of an anti-hypertensive agent, losartan potassium, using response surface methodology (RSM) by employing 32 full factorial design. Materials and Methods: Mucoadhesive buccal patches were prepared using different grades of hydroxypropyl methylcellulose (HPMC) (K4M and K100M) and polyvinylpyrrolidone-K30 by solvent casting method. The amount of the release retardant polymers – HPMC K4M (X1) and HPMC K100M (X2) was taken as an independent variable. The dependent variables were the burst release in 30 min (Y1), cumulative percentage release of drug after 8 h (Y2) and swelling index (Y3) of the patches. In vitro release and swelling studies were carried out and the data were fitted to kinetic equations. Results: The physicochemical, bioadhesive, and swelling properties of patches were found to vary significantly depending on the viscosity of the polymers and their combination. Patches showed an initial burst release preceding a more gradual sustained release phase following a nonfickian diffusion process. Discussion: The results indicate that suitable bioadhesive buccal patches with desired permeability could be prepared, facilitated with the RSM. PMID:26682205

  2. Design, formulation and optimization of novel soft nano-carriers for transdermal olmesartan medoxomil delivery: In vitro characterization and in vivo pharmacokinetic assessment.

    Kamran, Mohd; Ahad, Abdul; Aqil, Mohd; Imam, Syed Sarim; Sultana, Yasmin; Ali, Asgar

    2016-05-30

    Olmesartan is a hydrophobic antihypertensive drug with a short biological half-life, and low bioavailability, presents a challenge with respect to its oral administration. The objective of the work was to formulate, optimize and evaluate the transdermal potential of novel vesicular nano-invasomes, containing above anti-hypertensive agent. To achieve the above purpose, soft carriers (viz. nano-invasomes) of olmesartan with β-citronellene as potential permeation enhancer were developed and optimized using Box-Behnken design. The physicochemical characteristics e.g., vesicle size, shape, entrapment efficiency and skin permeability of the nano-invasomes formulations were evaluated. The optimized formulation was further evaluated for in vitro drug release, confocal microscopy and in vivo pharmacokinetic study. The optimum nano-invasomes formulation showed vesicles size of 83.35±3.25nm, entrapment efficiency of 65.21±2.25% and transdermal flux of 32.78±0.703 (μg/cm(2)/h) which were found in agreement with the predicted value generated by Box-Behnken design. Confocal laser microscopy of rat skin showed that optimized formulation was eventually distributed and permeated deep into the skin. The pharmacokinetic study presented that transdermal nano-invasomes formulation showed 1.15 times improvement in bioavailability of olmesartan with respect to the control formulation in Wistar rats. It was concluded that the response surfaces estimated by Design Expert(®) illustrated obvious relationship between formulation factors and response variables and nano-invasomes were found to be a proficient carrier system for transdermal delivery of olmesartan. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Systematic optimization of subcritical and transcritical organic Rankine cycles (ORCs) constrained by technical parameters in multiple applications

    Maraver, Daniel; Royo, Javier; Lemort, Vincent; Quoilin, Sylvain

    2014-01-01

    Highlights: • ORC optimization for different target applications. • Model developed to allow computation in subcritical and transcritical operation. • Regenerative and non-regenerative cycles evaluated through second law efficiency. • Common working fluids: R134a, R245fa, Solkatherm, n-Pentane, MDM, Toluene. • Thermodynamic and technological approaches lead to optimal design guidelines. - Abstract: The present work is focused on the thermodynamic optimization of organic Rankine cycles (ORCs) for power generation and CHP from different average heat source profiles (waste heat recovery, thermal oil for cogeneration and geothermal). The general goal is to provide optimization guidelines for a wide range of operating conditions, for subcritical and transcritical, regenerative and non-regenerative cycles. A parameter assessment of the main equipment in the cycle (expander, heat exchangers and feed pump) was also carried out. An optimization model of the ORC (available as an electronic annex) is proposed to predict the best cycle performance (subcritical or transcritical), in terms of its exergy efficiency, with different working fluids. The working fluids considered are those most commonly used in commercial ORC units (R134a, R245fa, Solkatherm, n-Pentane, Octamethyltrisiloxane and Toluene). The optimal working fluid and operating conditions from a purely thermodynamic approach are limited by the technological constraints of the expander, the heat exchangers and the feed pump. Hence, a complementary assessment of both approaches is more adequate to obtain some preliminary design guidelines for ORC units

  4. Formulation and statistical optimization of gastric floating alginate/oil/chitosan capsules loading procyanidins: in vitro and in vivo evaluations.

    Chen, Rencai; Guo, Xiaomin; Liu, Xuecong; Cui, Haiming; Wang, Rui; Han, Jing

    2018-03-01

    The aim of the present work was to develop gastric floating capsules containing oil-entrapped beads loading procyanidins. The floating beads were prepared by ionotropic gelation method using sodium alginate, CaCl 2 and chitosan. The effect of three independent parameters (concentration of sodium alginate, CaCl 2 and chitosan) on entrapment efficiency were analyzed by Box-Behnken design. The floating beads were evaluated for surface morphology, particle size, density, entrapment efficiency, buoyancy, release behavior in vitro and floating ability in vivo. The prepared beads were grossly spherical in shape and the mean size was approximately 1.54±0.17mm. The density was 0.97g/cm 3 . And the optimal conditions were as follows: concentration of sodium alginate, CaCl 2 and chitosan were 33.75mg/mL, 9.84mg/mL and 9.05mg/mL, respectively. The optimized formulation showed entrapment efficiency of 88.84±1.04% within small error-value (0.65). The release mechanism of floating capsules followed Korsmeyer-Peppas model (r 2 =0.9902) with non-Fickian release. The gastric floating capsules exhibited 100% floating percentage in vitro and they could float on the top of gastric juice for 5h in vivo. Therefore, the floating capsules are able to prolong the gastroretentive delivery of procyanidins. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Formulation, evaluation and 3(2) full factorial design-based optimization of ondansetron hydrochloride incorporated taste masked microspheres.

    Kharb, Vandana; Saharan, Vikas Anand; Dev, Kapil; Jadhav, Hemant; Purohit, Suresh

    2014-11-01

    Masking the bitter taste of Ondansetron hydrochloride (ONS) may improve palatability, acceptance and compliance of ONS products. ONS-loaded, taste-masked microspheres were prepared with a polycationic pH-sensitive polymer and 3(2) full factorial design (FFD) was applied to optimize microsphere batches. Solvent evaporation, in acetone--methanol/liquid paraffin system, was used to prepare taste-masked ONS microspheres. The effect of varying drug/polymer (D/P) ratios on microspheres characteristics were studied by 3(2) FFD. Desirability function was used to search the optimum formulation. Microspheres were evaluated by FTIR, XRD and DSC to examine interaction and effect of microencapsulation process. In vitro taste assessment approach based on bitterness threshold and drug release was used to assess bitterness scores. Prepared ONS microspheres were spherical and surface was wrinkled. ONS was molecularly dispersed in microspheres without any incompatibility with EE100. In hydrochloric acid buffer pH 1.2, ONS released completely from microsphere in just 10 min. Contrary to this, ONS release at initial 5 min from taste-masked microspheres was less than the bitterness threshold. Full factorial design and in vitro taste assessment approach, coupled together, was successfully applied to develop and optimize batches of ONS incorporated taste-masked microspheres.

  6. Development and optimization of solid lipid nanoparticle formulation for ophthalmic delivery of chloramphenicol using a Box-Behnken design

    Hao, Jifu; Fang, Xinsheng; Zhou, Yanfang; Wang, Jianzhu; Guo, Fengguang; Li, Fei; Peng, Xinsheng

    2011-01-01

    The purpose of the present study was to optimize a solid lipid nanoparticle (SLN) of chloramphenicol by investigating the relationship between design factors and experimental data using response surface methodology. A Box-Behnken design was constructed using solid lipid (X1), surfactant (X2), and drug/lipid ratio (X3) level as independent factors. SLN was successfully prepared by a modified method of melt-emulsion ultrasonication and low temperature-solidification technique using glyceryl monostearate as the solid lipid, and poloxamer 188 as the surfactant. The dependent variables were entrapment efficiency (EE), drug loading (DL), and turbidity. Properties of SLN such as the morphology, particle size, zeta potential, EE, DL, and drug release behavior were investigated, respectively. As a result, the nanoparticle designed showed nearly spherical particles with a mean particle size of 248 nm. The polydispersity index of particle size was 0.277 ± 0.058 and zeta potential was −8.74 mV. The EE (%) and DL (%) could reach up to 83.29% ± 1.23% and 10.11% ± 2.02%, respectively. In vitro release studies showed a burst release at the initial stage followed by a prolonged release of chloramphenicol from SLN up to 48 hours. The release kinetics of the optimized formulation best fitted the Peppas–Korsmeyer model. These results indicated that the chloramphenicol-loaded SLN could potentially be exploited as a delivery system with improved drug entrapment efficiency and controlled drug release. PMID:21556343

  7. Determining the Optimal Solution for Quadratically Constrained Quadratic Programming (QCQP) on Energy-Saving Generation Dispatch Problem

    Lesmana, E.; Chaerani, D.; Khansa, H. N.

    2018-03-01

    Energy-Saving Generation Dispatch (ESGD) is a scheme made by Chinese Government in attempt to minimize CO2 emission produced by power plant. This scheme is made related to global warming which is primarily caused by too much CO2 in earth’s atmosphere, and while the need of electricity is something absolute, the power plants producing it are mostly thermal-power plant which produced many CO2. Many approach to fulfill this scheme has been made, one of them came through Minimum Cost Flow in which resulted in a Quadratically Constrained Quadratic Programming (QCQP) form. In this paper, ESGD problem with Minimum Cost Flow in QCQP form will be solved using Lagrange’s Multiplier Method

  8. Constrained evolution in numerical relativity

    Anderson, Matthew William

    The strongest potential source of gravitational radiation for current and future detectors is the merger of binary black holes. Full numerical simulation of such mergers can provide realistic signal predictions and enhance the probability of detection. Numerical simulation of the Einstein equations, however, is fraught with difficulty. Stability even in static test cases of single black holes has proven elusive. Common to unstable simulations is the growth of constraint violations. This work examines the effect of controlling the growth of constraint violations by solving the constraints periodically during a simulation, an approach called constrained evolution. The effects of constrained evolution are contrasted with the results of unconstrained evolution, evolution where the constraints are not solved during the course of a simulation. Two different formulations of the Einstein equations are examined: the standard ADM formulation and the generalized Frittelli-Reula formulation. In most cases constrained evolution vastly improves the stability of a simulation at minimal computational cost when compared with unconstrained evolution. However, in the more demanding test cases examined, constrained evolution fails to produce simulations with long-term stability in spite of producing improvements in simulation lifetime when compared with unconstrained evolution. Constrained evolution is also examined in conjunction with a wide variety of promising numerical techniques, including mesh refinement and overlapping Cartesian and spherical computational grids. Constrained evolution in boosted black hole spacetimes is investigated using overlapping grids. Constrained evolution proves to be central to the host of innovations required in carrying out such intensive simulations.

  9. Application of experimental design in examination of the dissolution rate of carbamazepine from formulations: Characterization of the optimal formulation by DSC, TGA, FT-IR and PXRD analysis

    Krstić Marko; Ražić Slavica; Vasiljević Dragana; Spasojević Đurđija; Ibrić Svetlana

    2015-01-01

    Poor solubility is one of the key reasons for the poor bioavailability of these drugs. This paper displays a formulation of a solid surfactant system with carbamazepine, in order to increase its dissolution rate. Solid state surfactant systems are formed by application of fractal experimental design. Poloxamer 237 and Poloxamer 338 were used as surfactants and Brij® 35 was used as the co-surfactant. The ratios of the excipients and carbamazepine were varied...

  10. Pilot signal design via constrained optimization with application to delay-Doppler shift estimation in OFDM systems

    Jing, Lishuai; Pedersen, Troels; Fleury, Bernard Henri

    2013-01-01

    for which we propose a genetic algorithm that computes close-to-optimal solutions. Simulation results demonstrate that the proposed algorithm can efficiently find pilot signals that outperform the state-of-the-art pilot signals in both single-path and multipath propagation scenarios. In addition, we...

  11. An algorithm for mass matrix calculation of internally constrained molecular geometries.

    Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

    2008-01-28

    Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

  12. An algorithm for mass matrix calculation of internally constrained molecular geometries

    Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

    2008-01-01

    Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model

  13. Cost-constrained optimal sampling for system identification in pharmacokinetics applications with population priors and nuisance parameters.

    Sorzano, Carlos Oscars S; Pérez-De-La-Cruz Moreno, Maria Angeles; Burguet-Castell, Jordi; Montejo, Consuelo; Ros, Antonio Aguilar

    2015-06-01

    Pharmacokinetics (PK) applications can be seen as a special case of nonlinear, causal systems with memory. There are cases in which prior knowledge exists about the distribution of the system parameters in a population. However, for a specific patient in a clinical setting, we need to determine her system parameters so that the therapy can be personalized. This system identification is performed many times by measuring drug concentrations in plasma. The objective of this work is to provide an irregular sampling strategy that minimizes the uncertainty about the system parameters with a fixed amount of samples (cost constrained). We use Monte Carlo simulations to estimate the average Fisher's information matrix associated to the PK problem, and then estimate the sampling points that minimize the maximum uncertainty associated to system parameters (a minimax criterion). The minimization is performed employing a genetic algorithm. We show that such a sampling scheme can be designed in a way that is adapted to a particular patient and that it can accommodate any dosing regimen as well as it allows flexible therapeutic strategies. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

  14. Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

    Elsays, Mostafa A.; Naguib Aly, M; Badawi, Alya A.

    2010-01-01

    The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Mult-objective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem. (orig.)

  15. MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

    Liu, X; Belcher, AH; Wiersma, R [The University of Chicago, Chicago, IL (United States)

    2016-06-15

    Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimization and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also

  16. Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

    Delbos, F.

    2004-11-01

    Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

  17. Optimization of radiotherapy to target volumes with concave outlines: target-dose homogenization and selective sparing of critical structures by constrained matrix inversion

    Colle, C; Van den Berge, D; De Wagter, C; Fortan, L; Van Duyse, B; De Neve, W

    1995-12-01

    The design of 3D-conformal dose distributions for targets with concave outlines is a technical challenge in conformal radiotherapy. For these targets, it is impossible to find beam incidences for which the target volume can be isolated from the tissues at risk. Commonly occurring examples are most thyroid cancers and the targets located at the lower neck and upper mediastinal levels related to some head and neck. A solution to this problem was developed, using beam intensity modulation executed with a multileaf collimator by applying a static beam-segmentation technique. The method includes the definition of beam incidences and beam segments of specific shape as well as the calculation of segment weights. Tests on Sherouse`s GRATISTM planning system allowed to escalate the dose to these targets to 65-70 Gy without exceeding spinal cord tolerance. Further optimization by constrained matrix inversion was investigated to explore the possibility of further dose escalation.

  18. Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

    Delbos, F

    2004-11-01

    Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

  19. Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

    Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

    2017-05-01

    In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

    Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

    2017-05-01

    In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

  1. Formulation, optimization, and in vitro/in vivo evaluation of furosemide nanosuspension for enhancement of its oral bioavailability

    Sahu, Bhanu P.; Das, Malay K.

    2014-04-01

    Furosemide is a poorly soluble diuretic used for treatment of hypertension and edema. It has very poor or variable oral bioavailability due to its reduced solubility in gastric fluid and reduced permeability in intestinal fluid. The aim of this study was to prepare nanosuspension of furosemide to enhance its oral bioavailability by increasing its dissolution in stomach where it has better permeability. Full factorial design was used for a systematic approach of formulation and optimization. The nanosuspensions were prepared by precipitation with ultrasonication method. Polyvinyl acetate was used for sterically stabilizing the nanosuspensions. The diffusing drug concentration and stabilizer were used as the factors and the particle size, polydispersity index, and drug release were selected as dependent variables and characterized. The effect of nanoprecipitation on enhancement of oral bioavailability of furosemide nanosuspension was studied by in vitro dissolution and in vivo absorption studies in rats and compared to pure drug. Quality by design using full factorial design provided a systematic approach in optimizing nanosuspensions to produce products with desired quality. Stable nanosuspension were obtained with average size range of the precipitated nanoparticles between 150 and 300 nm and were found to be homogenous showing a narrow polydispersity index of 0.3 ± 0.1. The in vivo studies on rats revealed a significant increase in the oral absorbtion of furosemide in the nanosuspension compared to pure drug. The AUC0→24 and C max values of nanosuspension were approximately 1.38- and 1.68-fold greater than that of pure drug, respectively. Furosemide nanosuspension showed 20.06 ± 0.02 % decrease in systolic blood pressure compared to 13.37 + 0.02 % in plain furosemide suspension, respectively. The improved oral bioavailability and pharmacodynamic effect of furosemide may be due to the improved dissolution of furosemide in simulated gastric fluid which results

  2. A constrained extended Kalman filter for the optimal estimate of kinematics and kinetics of a sagittal symmetric exercise.

    Bonnet, V; Dumas, R; Cappozzo, A; Joukov, V; Daune, G; Kulić, D; Fraisse, P; Andary, S; Venture, G

    2017-09-06

    This paper presents a method for real-time estimation of the kinematics and kinetics of a human body performing a sagittal symmetric motor task, which would minimize the impact of the stereophotogrammetric soft tissue artefacts (STA). The method is based on a bi-dimensional mechanical model of the locomotor apparatus the state variables of which (joint angles, velocities and accelerations, and the segments lengths and inertial parameters) are estimated by a constrained extended Kalman filter (CEKF) that fuses input information made of both stereophotogrammetric and dynamometric measurement data. Filter gains are made to saturate in order to obtain plausible state variables and the measurement covariance matrix of the filter accounts for the expected STA maximal amplitudes. We hypothesised that the ensemble of constraints and input redundant information would allow the method to attenuate the STA propagation to the end results. The method was evaluated in ten human subjects performing a squat exercise. The CEKF estimated and measured skin marker trajectories exhibited a RMS difference lower than 4mm, thus in the range of STAs. The RMS differences between the measured ground reaction force and moment and those estimated using the proposed method (9N and 10Nm) were much lower than obtained using a classical inverse dynamics approach (22N and 30Nm). From the latter results it may be inferred that the presented method allows for a significant improvement of the accuracy with which kinematic variables and relevant time derivatives, model parameters and, therefore, intersegmental moments are estimated. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization

    Branda, Martin; Bucher, M.; Červinka, Michal; Schwartz, A.

    2018-01-01

    Roč. 70, č. 2 (2018), s. 503-530 ISSN 0926-6003 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Cardinality constraints * Regularization method * Scholtes regularization * Strong stationarity * Sparse portfolio optimization * Robust portfolio optimization Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 1.520, year: 2016 http://library.utia.cas.cz/separaty/2018/MTR/branda-0489264.pdf

  4. Optimization of the formulation for preparing Lactobacillus casei loaded whey protein-Ca-alginate microparticles using full-factorial design.

    Smilkov, Katarina; Petreska Ivanovska, Tanja; Petrushevska Tozi, Lidija; Petkovska, Rumenka; Hadjieva, Jasmina; Popovski, Emil; Stafilov, Trajce; Grozdanov, Anita; Mladenovska, Kristina

    2014-01-01

    This article presents specific approach for microencapsulation of Lactobacillus casei using emulsion method followed by additional coating with whey protein. Experimental design was employed using polynomial regression model at 2nd level with three independent variables, concentrations of alginate, whey protein and CaCl2. Physicochemical, biopharmaceutical and biological properties were investigated. In 11 series generated, negatively charged microparticles were obtained, with size 6.99-9.88 µm, Ca-content 0.29-0.47 mg per 10 mg microparticles, and viability of the probiotic 9.30-10.87 log10CFU/g. The viability after 24 hours in simulated gastrointestinal conditions was between 3.60 and 8.32 log10CFU/g. Optimal formulation of the microparticles that ensures survival of the probiotic and achieves controlled delivery was determined: 2.5% (w/w) alginate, 3% (w/w) CaCl2 and 3% (w/w) whey protein. The advantageous properties of the L. casei-loaded microparticles make them suitable for incorporation in functional food and/or pharmaceutical products.

  5. Accurate, rapid identification of dislocation lines in coherent diffractive imaging via a min-max optimization formulation

    Ulvestad, A. [Materials Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Menickelly, M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Wild, S. M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA

    2018-01-01

    Defects such as dislocations impact materials properties and their response during external stimuli. Imaging these defects in their native operating conditions to establish the structure-function relationship and, ultimately, to improve performance via defect engineering has remained a considerable challenge for both electron-based and x-ray-based imaging techniques. While Bragg coherent x-ray diffractive imaging (BCDI) is successful in many cases, nuances in identifying the dislocations has left manual identification as the preferred method. Derivative-based methods are also used, but they can be inaccurate and are computationally inefficient. Here we demonstrate a derivative-free method that is both more accurate and more computationally efficient than either derivative-or human-based methods for identifying 3D dislocation lines in nanocrystal images produced by BCDI. We formulate the problem as a min-max optimization problem and show exceptional accuracy for experimental images. We demonstrate a 227x speedup for a typical experimental dataset with higher accuracy over current methods. We discuss the possibility of using this algorithm as part of a sparsity-based phase retrieval process. We also provide MATLAB code for use by other researchers.

  6. Systemic study of solvent-assisted active loading of gambogic acid into liposomes and its formulation optimization for improved delivery.

    Tang, Wei-Lun; Tang, Wei-Hsin; Szeitz, Andras; Kulkarni, Jayesh; Cullis, Pieter; Li, Shyh-Dar

    2018-06-01

    The solvent-assisted active loading technology (SALT) was developed for encapsulating a water insoluble weak base into the liposomal core in the presence of 5% DMSO. In this study, we further examined the effect of various water miscible solvents in promoting active loading of other types of drugs into liposomes. To achieve complete drug loading, the amount of solvent required must result in complete drug solubilization and membrane permeability enhancement, but must be below the threshold that induces liposomal aggregation or causes bilayer disruption. We then used the SALT to load gambogic acid (GA, an insoluble model drug that shows promising anticancer effect) into liposomes, and optimized the loading gradient and lipid composition to prepare a stable formulation (Lipo-GA) that displayed >95% drug retention after incubation with serum for 3 days. Lipo-GA contained a high drug-to-lipid ratio of 1/5 (w/w) with a mean particle size of ∼75 nm. It also displayed a prolonged circulation half-life (1.5 h vs. 18.6 h) and enhanced antitumor activity in two syngeneic mice models compared to free GA. Particularly, complete tumor regression was observed in the EMT6 tumor model for 14 d with significant inhibition of multiple oncogenes including HIF-1α, VEGF-A, STAT3, BCL-2, and NF-κB. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Quality by Design (QbD) approach to optimize the formulation of a bilayer combination tablet (Telmiduo®) manufactured via high shear wet granulation.

    Lee, Ah Ram; Kwon, Seok Young; Choi, Du Hyung; Park, Eun Seok

    2017-12-20

    A bilayer tablet, which consisted of telmisartan and amlodipine besylate, was formulated based on a Quality by Design (QbD) approach. The control and response factors were determined based on primary knowledge and the target values of the control tablet (Twynsta ® ). A D-optimal mixture design was used to obtain the optimal formulations in terms of D-mannitol, crospovidone, and MCC for the telmisartan layer, and CCM-Na, PVP K25, and Prosolv for the amlodipine layer. The quantitative effects of the different formulation factors on the response factors were accurately predicted using the equations of best fit and a strong linearity was observed between the predicted and actual values of the response factors. The optimized bilayer tablet was obtained using a numeric optimization technique and was characterized compared with a control (Twynsta ® ) by using various physical evaluations and in vivo pharmacokinetic parameters. The physical stability of Telmiduo ® was greater than that of Twynsta ® owing to the improvement of formulation factors. The in vivo pharmacokinetic parameters suggested that Telmiduo ® might have pharmaceutical equivalence and bioequivalence with Twynsta ® . Therefore, the bilayer tablet that consisted of telmisartan and amlodipine besylate could be produced using a more economical and simpler method than that used to produce Twynsta ® . Moreover, the suitability of QbD for effective product development in the pharmaceutical industry was shown. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. The Incompatibility of Pareto Optimality and Dominant-Strategy Incentive Compatibility in Sufficiently-Anonymous Budget-Constrained Quasilinear Settings

    Rica Gonen

    2013-11-01

    Full Text Available We analyze the space of deterministic, dominant-strategy incentive compatible, individually rational and Pareto optimal combinatorial auctions. We examine a model with multidimensional types, nonidentical items, private values and quasilinear preferences for the players with one relaxation; the players are subject to publicly-known budget constraints. We show that the space includes dictatorial mechanisms and that if dictatorial mechanisms are ruled out by a natural anonymity property, then an impossibility of design is revealed. The same impossibility naturally extends to other abstract mechanisms with an arbitrary outcome set if one maintains the original assumptions of players with quasilinear utilities, public budgets and nonnegative prices.

  9. How cholesterol constrains glycolipid conformation for optimal recognition of Alzheimer's beta amyloid peptide (Abeta1-40).

    Yahi, Nouara; Aulas, Anaïs; Fantini, Jacques

    2010-02-05

    Membrane lipids play a pivotal role in the pathogenesis of Alzheimer's disease, which is associated with conformational changes, oligomerization and/or aggregation of Alzheimer's beta-amyloid (Abeta) peptides. Yet conflicting data have been reported on the respective effect of cholesterol and glycosphingolipids (GSLs) on the supramolecular assembly of Abeta peptides. The aim of the present study was to unravel the molecular mechanisms by which cholesterol modulates the interaction between Abeta(1-40) and chemically defined GSLs (GalCer, LacCer, GM1, GM3). Using the Langmuir monolayer technique, we show that Abeta(1-40) selectively binds to GSLs containing a 2-OH group in the acyl chain of the ceramide backbone (HFA-GSLs). In contrast, Abeta(1-40) did not interact with GSLs containing a nonhydroxylated fatty acid (NFA-GSLs). Cholesterol inhibited the interaction of Abeta(1-40) with HFA-GSLs, through dilution of the GSL in the monolayer, but rendered the initially inactive NFA-GSLs competent for Abeta(1-40) binding. Both crystallographic data and molecular dynamics simulations suggested that the active conformation of HFA-GSL involves a H-bond network that restricts the orientation of the sugar group of GSLs in a parallel orientation with respect to the membrane. This particular conformation is stabilized by the 2-OH group of the GSL. Correspondingly, the interaction of Abeta(1-40) with HFA-GSLs is strongly inhibited by NaF, an efficient competitor of H-bond formation. For NFA-GSLs, this is the OH group of cholesterol that constrains the glycolipid to adopt the active L-shape conformation compatible with sugar-aromatic CH-pi stacking interactions involving residue Y10 of Abeta(1-40). We conclude that cholesterol can either inhibit or facilitate membrane-Abeta interactions through fine tuning of glycosphingolipid conformation. These data shed some light on the complex molecular interplay between cell surface GSLs, cholesterol and Abeta peptides, and on the influence

  10. How cholesterol constrains glycolipid conformation for optimal recognition of Alzheimer's beta amyloid peptide (Abeta1-40.

    Nouara Yahi

    Full Text Available Membrane lipids play a pivotal role in the pathogenesis of Alzheimer's disease, which is associated with conformational changes, oligomerization and/or aggregation of Alzheimer's beta-amyloid (Abeta peptides. Yet conflicting data have been reported on the respective effect of cholesterol and glycosphingolipids (GSLs on the supramolecular assembly of Abeta peptides. The aim of the present study was to unravel the molecular mechanisms by which cholesterol modulates the interaction between Abeta(1-40 and chemically defined GSLs (GalCer, LacCer, GM1, GM3. Using the Langmuir monolayer technique, we show that Abeta(1-40 selectively binds to GSLs containing a 2-OH group in the acyl chain of the ceramide backbone (HFA-GSLs. In contrast, Abeta(1-40 did not interact with GSLs containing a nonhydroxylated fatty acid (NFA-GSLs. Cholesterol inhibited the interaction of Abeta(1-40 with HFA-GSLs, through dilution of the GSL in the monolayer, but rendered the initially inactive NFA-GSLs competent for Abeta(1-40 binding. Both crystallographic data and molecular dynamics simulations suggested that the active conformation of HFA-GSL involves a H-bond network that restricts the orientation of the sugar group of GSLs in a parallel orientation with respect to the membrane. This particular conformation is stabilized by the 2-OH group of the GSL. Correspondingly, the interaction of Abeta(1-40 with HFA-GSLs is strongly inhibited by NaF, an efficient competitor of H-bond formation. For NFA-GSLs, this is the OH group of cholesterol that constrains the glycolipid to adopt the active L-shape conformation compatible with sugar-aromatic CH-pi stacking interactions involving residue Y10 of Abeta(1-40. We conclude that cholesterol can either inhibit or facilitate membrane-Abeta interactions through fine tuning of glycosphingolipid conformation. These data shed some light on the complex molecular interplay between cell surface GSLs, cholesterol and Abeta peptides, and on the

  11. Workshop on Computational Optimization

    2015-01-01

    Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2013. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, resource constrained project scheduling, problems arising in transport services, error correcting codes, optimal system performance and energy consumption and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others.

  12. Sensor Networks for Optimal Target Localization with Bearings-Only Measurements in Constrained Three-Dimensional Scenarios

    Joaquin Aranda

    2013-08-01

    Full Text Available In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.

  13. Sensor networks for optimal target localization with bearings-only measurements in constrained three-dimensional scenarios.

    Moreno-Salinas, David; Pascoal, Antonio; Aranda, Joaquin

    2013-08-12

    In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix) to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.

  14. Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds

    Raffensperger, Jeff P.; Baker, Anna C.; Blomquist, Joel D.; Hopple, Jessica A.

    2017-06-26

    Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point.Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased

  15. Spray-drying nanocapsules in presence of colloidal silica as drying auxiliary agent: formulation and process variables optimization using experimental designs.

    Tewa-Tagne, Patrice; Degobert, Ghania; Briançon, Stéphanie; Bordes, Claire; Gauvrit, Jean-Yves; Lanteri, Pierre; Fessi, Hatem

    2007-04-01

    Spray-drying process was used for the development of dried polymeric nanocapsules. The purpose of this research was to investigate the effects of formulation and process variables on the resulting powder characteristics in order to optimize them. Experimental designs were used in order to estimate the influence of formulation parameters (nanocapsules and silica concentrations) and process variables (inlet temperature, spray-flow air, feed flow rate and drying air flow rate) on spray-dried nanocapsules when using silica as drying auxiliary agent. The interactions among the formulation parameters and process variables were also studied. Responses analyzed for computing these effects and interactions were outlet temperature, moisture content, operation yield, particles size, and particulate density. Additional qualitative responses (particles morphology, powder behavior) were also considered. Nanocapsules and silica concentrations were the main factors influencing the yield, particulate density and particle size. In addition, they were concerned for the only significant interactions occurring among two different variables. None of the studied variables had major effect on the moisture content while the interaction between nanocapsules and silica in the feed was of first interest and determinant for both the qualitative and quantitative responses. The particles morphology depended on the feed formulation but was unaffected by the process conditions. This study demonstrated that drying nanocapsules using silica as auxiliary agent by spray drying process enables the obtaining of dried micronic particle size. The optimization of the process and the formulation variables resulted in a considerable improvement of product yield while minimizing the moisture content.

  16. Simulation of global oceanic upper layers forced at the surface by an optimal bulk formulation derived from multi-campaign measurements.

    Garric, G.; Pirani, A.; Belamari, S.; Caniaux, G.

    2006-12-01

    order to improve the air/sea interface for the future MERCATOR global ocean operational system, we have implemented the new bulk formulation developed by METEO-FRANCE (French Meteo office) in the MERCATOR 2 degree global ocean-ice coupled model (ORCA2/LIM). A single bulk formulation for the drag, temperature and moisture exchange coefficients is derived from an extended consistent database gathering 10 years of measurements issued from five experiments dedicated to air-sea fluxes estimates (SEMAPHORE, CATCH, FETCH, EQUALANT99 and POMME) in various oceanic basins (from Northern to equatorial Atlantic). The available database (ALBATROS) cover the widest range of atmospheric and oceanic conditions, from very light (0.3 m/s) to very strong (up to 29 m/s) wind speeds, and from unstable to extremely stable atmospheric boundary layer stratification. We have defined a work strategy to test this new formulation in a global oceanic context, by using this multi- campaign bulk formulation to derive air-sea fluxes from base meteorological variables produces by the ECMWF (European Centre for Medium Range and Weather Forecast) atmospheric forecast model, in order to get surface boundary conditions for ORCA2/LIM. The simulated oceanic upper layers forced at the surface by the previous air/sea interface are compared to those forced by the optimal bulk formulation. Consecutively with generally weaker transfer coefficient, the latter formulation reduces the cold bias in the equatorial Pacific and increases the too weak summer sea ice extent in Antarctica. Compared to a recent mixed layer depth (MLD) climatology, the optimal bulk formulation reduces also the too deep simulated MLDs. Comparison with in situ temperature and salinity profiles in different areas allowed us to evaluate the impact of changing the air/sea interface in the vertical structure.

  17. Formulation of cilostazol spherical agglomerates by crystallo-co-agglomeration technique and optimization using design of experimentation.

    Deshkar, Sanjeevani Shekhar; Borde, Govind R; Kale, Rupali N; Waghmare, Balasaheb A; Thomas, Asha Biju

    2017-01-01

    Spherical agglomeration is one of the novel techniques for improvement of flow and dissolution properties of drugs. Cilostazol is a biopharmaceutics classification system Class II drug with poor solubility resulting in limited bioavailability. The present study aims at improving the solubility and dissolution of cilostazol by crystallo-co-agglomeration technique. Cilostazol agglomerates were prepared using various polymers with varying concentration of hydroxypropyl methylcellulose E 50 (HPMC E50), polyvinyl pyrrolidone K30 (PVP K30), and polyethylene glycol 6000. The influence of polymer concentration on spherical agglomerate formation was studied by 3 2 factorial design. Cilostazol agglomerates were evaluated for percent yield, mean particle size, drug content, aqueous solubility, and in vitro dissolution and further characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and X-ray diffraction (XRD). The agglomeration process resulted in optimized formulation, F3 with mean agglomerate size of 210.0 ± 0.56 μm, excellent flow properties, approximately 15-fold increase in solubility than pure cilostazol and complete drug release in 60 min. Process yield, agglomerate size, and drug release were affected by amount of PVP K 30 and HPMC E50. The presence of drug microcrystal was confirmed by SEM, whereas FTIR study indicated no chemical change. Increase in drug solubility was attributed to change of crystalline drug to amorphous form that is evident in DSC and XRD. Crystallo-co-agglomeration can be adopted as an important approach for increasing the solubility and dissolution of poorly soluble drug.

  18. Optimization of methotrexate loaded niosomes by Box-Behnken design: an understanding of solvent effect and formulation variability.

    Zidan, Ahmed S; Mokhtar Ibrahim, Mahmoud; Megrab, Nagia A El

    2017-09-01

    Dermal drug delivery system which localizes methotrexate (MTX) in the skin is advantageous in topical treatment of psoriasis. The aim of the current study was to understand dilution effects and formulation variability for the potential formation of niosomes from proniosome gels of MTX. Box-Behnken's design was employed to prepare a series of MTX proniosome gels of Span 40, cholesterol (Chol-X 1 ) and Tween 20 (T20-X 2 ). Short chain alcohols (X 3 ), namely ethanol (Et), propylene glycol (Pg) and glycerol (G) were evaluated for their dilution effects on proniosomes. The responses investigated were niosomal vesicles size (Y 1 ), MTX entrapment efficiency percent (EE%-Y 2 ) and zeta potential (Y 3 ). MTX loaded niosomes were formed immediately upon hydration of the proniosome gels with the employed solvents. Addition of Pg resulted in a decrease of vesicular size from 534 nm to 420 nm as Chol percentage increased from 10% to 30%, respectively. In addition, increasing the hydrophilicity of the employed solvents was enhancing the resultant zeta potential. On the other hand, using Et in proniosomal gels would abolish Chol action to increase the zeta potential value and hence less stable niosomal dispersion was formed. The optimized formula of MTX loaded niosomes showed vesicle size of 480 nm, high EE% (55%) and zeta potential of -25.5 mV, at Chol and T20 concentrations of 30% and 23.6%, respectively, when G was employed as the solvent. Hence, G was the solvent of choice to prepare MTX proniosomal gels with a maintained stability and highest entrapment.

  19. Application of experimental design in examination of the dissolution rate of carbamazepine from formulations: Characterization of the optimal formulation by DSC, TGA, FT-IR and PXRD analysis

    Krstić Marko

    2015-01-01

    Full Text Available Poor solubility is one of the key reasons for the poor bioavailability of these drugs. This paper displays a formulation of a solid surfactant system with carbamazepine, in order to increase its dissolution rate. Solid state surfactant systems are formed by application of fractal experimental design. Poloxamer 237 and Poloxamer 338 were used as surfactants and Brij® 35 was used as the co-surfactant. The ratios of the excipients and carbamazepine were varied and their effects on the dissolution rate of carbamazepine were examined. Moreover, the effects of the addition of natural (diatomite and a synthetic adsorbent carrier (Neusiline UFL2 on the dissolution rate of carbamazepine were also tested. The prepared surfactant systems were characterized and the influence of the excipients on possible changes of the polymorphous form of carbamazepine examined by application of analytical techniques (DSC, TGA, FT-IR, PXRD. It was determined that an appropriate selection of the excipient type and ratio could provide a significant increase in the carbamazepine dissolution rate. By application of analytical techniques, it was found that that the employed excipients induce a transition of carbamazepine into the amorphous form and that the selected sample was stable for three months, when kept under ambient conditions. [Projekat Ministarstva nauke Republike Srbije, br. TR34007

  20. Pole shifting with constrained output feedback

    Hamel, D.; Mensah, S.; Boisvert, J.

    1984-03-01

    The concept of pole placement plays an important role in linear, multi-variable, control theory. It has received much attention since its introduction, and several pole shifting algorithms are now available. This work presents a new method which allows practical and engineering constraints such as gain limitation and controller structure to be introduced right into the pole shifting design strategy. This is achieved by formulating the pole placement problem as a constrained optimization problem. Explicit constraints (controller structure and gain limits) are defined to identify an admissible region for the feedback gain matrix. The desired pole configuration is translated into an appropriate cost function which must be closed-loop minimized. The resulting constrained optimization problem can thus be solved with optimization algorithms. The method has been implemented as an algorithmic interactive module in a computer-aided control system design package, MVPACK. The application of the method is illustrated to design controllers for an aircraft and an evaporator. The results illustrate the importance of controller structure on overall performance of a control system

  1. Understanding and optimizing the dual excipient functionality of sodium lauryl sulfate in tablet formulation of poorly water soluble drug: wetting and lubrication.

    Aljaberi, Ahmad; Chatterji, Ashish; Dong, Zedong; Shah, Navnit H; Malick, Waseem; Singhal, Dharmendra; Sandhu, Harpreet K

    2013-01-01

    To evaluate and optimize sodium lauryl sulfate (SLS) and magnesium stearate (Mg.St) levels, with respect to dissolution and compaction, in a high dose, poorly soluble drug tablet formulation. A model poorly soluble drug was formulated using high shear aqueous granulation. A D-optimal design was used to evaluate and model the effect of granulation conditions, size of milling screen, SLS and Mg.St levels on tablet compaction and ejection. The compaction profiles were generated using a Presster(©) compaction simulator. Dissolution of the kernels was performed using a USP dissolution apparatus II and intrinsic dissolution was determined using a stationary disk system. Unlike kernels dissolution which failed to discriminate between tablets prepared with various SLS contents, the intrinsic dissolution rate showed that a SLS level of 0.57% was sufficient to achieve the required release profile while having minimal effect on compaction. The formulation factors that affect tablet compaction and ejection were identified and satisfactorily modeled. The design space of best factor setting to achieve optimal compaction and ejection properties was successfully constructed by RSM analysis. A systematic study design helped identify the critical factors and provided means to optimize the functionality of key excipient to design robust drug product.

  2. Enhancement of dissolution and oral bioavailability of lacidipine via pluronic P123/F127 mixed polymeric micelles: formulation, optimization using central composite design and in vivo bioavailability study.

    Fares, Ahmed R; ElMeshad, Aliaa N; Kassem, Mohamed A A

    2018-11-01

    This study aims at preparing and optimizing lacidipine (LCDP) polymeric micelles using thin film hydration technique in order to overcome LCDP solubility-limited oral bioavailability. A two-factor three-level central composite face-centered design (CCFD) was employed to optimize the formulation variables to obtain LCDP polymeric micelles of high entrapment efficiency and small and uniform particle size (PS). Formulation variables were: Pluronic to drug ratio (A) and Pluronic P123 percentage (B). LCDP polymeric micelles were assessed for entrapment efficiency (EE%), PS and polydispersity index (PDI). The formula with the highest desirability (0.959) was chosen as the optimized formula. The values of the formulation variables (A and B) in the optimized polymeric micelles formula were 45% and 80%, respectively. Optimum LCDP polymeric micelles had entrapment efficiency of 99.23%, PS of 21.08 nm and PDI of 0.11. Optimum LCDP polymeric micelles formula was physically characterized using transmission electron microscopy. LCDP polymeric micelles showed saturation solubility approximately 450 times that of raw LCDP in addition to significantly enhanced dissolution rate. Bioavailability study of optimum LCDP polymeric micelles formula in rabbits revealed a 6.85-fold increase in LCDP bioavailability compared to LCDP oral suspension.

  3. New scale-down methodology from commercial to lab scale to optimize plant-derived soft gel capsule formulations on a commercial scale.

    Oishi, Sana; Kimura, Shin-Ichiro; Noguchi, Shuji; Kondo, Mio; Kondo, Yosuke; Shimokawa, Yoshiyuki; Iwao, Yasunori; Itai, Shigeru

    2018-01-15

    A new scale-down methodology from commercial rotary die scale to laboratory scale was developed to optimize a plant-derived soft gel capsule formulation and eventually manufacture superior soft gel capsules on a commercial scale, in order to reduce the time and cost for formulation development. Animal-derived and plant-derived soft gel film sheets were prepared using an applicator on a laboratory scale and their physicochemical properties, such as tensile strength, Young's modulus, and adhesive strength, were evaluated. The tensile strength of the animal-derived and plant-derived soft gel film sheets was 11.7 MPa and 4.41 MPa, respectively. The Young's modulus of the animal-derived and plant-derived soft gel film sheets was 169 MPa and 17.8 MPa, respectively, and both sheets showed a similar adhesion strength of approximately 4.5-10 MPa. Using a D-optimal mixture design, plant-derived soft gel film sheets were prepared and optimized by varying their composition, including variations in the mass of κ-carrageenan, ι-carrageenan, oxidized starch and heat-treated starch. The physicochemical properties of the sheets were evaluated to determine the optimal formulation. Finally, plant-derived soft gel capsules were manufactured using the rotary die method and the prepared soft gel capsules showed equivalent or superior physical properties compared with pre-existing soft gel capsules. Therefore, we successfully developed a new scale-down methodology to optimize the formulation of plant-derived soft gel capsules on a commercial scale. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Workshop on Computational Optimization

    2016-01-01

    This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2014, held at Warsaw, Poland, September 7-10, 2014. The book presents recent advances in computational optimization. The volume includes important real problems like parameter settings for controlling processes in bioreactor and other processes, resource constrained project scheduling, infection distribution, molecule distance geometry, quantum computing, real-time management and optimal control, bin packing, medical image processing, localization the abrupt atmospheric contamination source and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.

  5. Optimal interpolation schemes to constrain pmPM2.5 in regional modeling over the United States

    Sousan, Sinan Dhia Jameel

    This thesis presents the use of data assimilation with optimal interpolation (OI) to develop atmospheric aerosol concentration estimates for the United States at high spatial and temporal resolutions. Concentration estimates are highly desirable for a wide range of applications, including visibility, climate, and human health. OI is a viable data assimilation method that can be used to improve Community Multiscale Air Quality (CMAQ) model fine particulate matter (PM2.5) estimates. PM2.5 is the mass of solid and liquid particles with diameters less than or equal to 2.5 µm suspended in the gas phase. OI was employed by combining model estimates with satellite and surface measurements. The satellite data assimilation combined 36 x 36 km aerosol concentrations from CMAQ with aerosol optical depth (AOD) measured by MODIS and AERONET over the continental United States for 2002. Posterior model concentrations generated by the OI algorithm were compared with surface PM2.5 measurements to evaluate a number of possible data assimilation parameters, including model error, observation error, and temporal averaging assumptions. Evaluation was conducted separately for six geographic U.S. regions in 2002. Variability in model error and MODIS biases limited the effectiveness of a single data assimilation system for the entire continental domain. The best combinations of four settings and three averaging schemes led to a domain-averaged improvement in fractional error from 1.2 to 0.97 and from 0.99 to 0.89 at respective IMPROVE and STN monitoring sites. For 38% of OI results, MODIS OI degraded the forward model skill due to biases and outliers in MODIS AOD. Surface data assimilation combined 36 × 36 km aerosol concentrations from the CMAQ model with surface PM2.5 measurements over the continental United States for 2002. The model error covariance matrix was constructed by using the observational method. The observation error covariance matrix included site representation that

  6. Optimization of the production process of a lyophilized formulation for radiopharmaceutical obtaining 99mTc-EDDA/HYNIC-E-[c(RGDfK)]2

    Sanchez R, S.

    2013-01-01

    In this work was optimized the production process of a lyophilized pharmaceutical formulation for the preparation of radiopharmaceutical 99m Tc-EDDA/HYNIC-E-[c(RGDfK)] 2 , the union specifies to the integrin s α v β 3 was demonstrated to be used in the nuclear medicine cabinets in the obtaining of scan images for the opportune detection of breast cancer. The good lyophilized pharmaceutical formulation for the preparation of radiopharmaceutical 99m Tc-EDDA/HYNIC-E-[c(RGDfK)] 2 was established like: HYNIC-E-[c(RGDfK)] 2 - 25 μg; Stannous chloride (SnCl 2 ) 20 μg; Ethylenediamine diacetic acid (EDDA) 10 mg; N-tris(hydroxymethyl)methyl glycin (Tricine) 20 mg; Mannitol 50 mg. The results of radiochemical purity of the sterile formulation and free of bacterial endotoxins for the three validation lots prepared under protocols of good manufacturing practices were 97.62 ± 1.48%, 96.54 ± 1.89%, and 97.66 ± 0.57%, for what the production procedure complies the predefined specifications. The radiopharmaceutical 99m Tc-EDDA/HYNIC-E-[c(RGDfK)]2 prepared from the lyophilized pharmaceutical formulation showed to be stable during a period 24 hours, for what can be used in the centers of molecular nuclear medicine. Images in vivo were obtained of the integrin s over-expression α v β 3 from the radiopharmaceutical 99m Tc-EDDA/HYNIC-E-[c(RGDfK)]2 obtained of the lyophilized and optimized pharmaceutical formulation. The lyophilized pharmaceutical formulation (HYNIC-RGD-Sn) showed stability during 12 months, due to this factor, is requested before the COFEPRIS the radiopharmaceutical expiration for this same period (accession number 123300401A0155). (Author)

  7. THE STUDY ON THE EFFECT OF FORMULATION VARIABLES ON IN VITRO FLOATING TIME AND THE RELEASE PROPERTIES OF A FLOATING DRUG DELIVERY SYSTEM BY A STATISTICAL OPTIMIZATION TECHNIQUE

    C. NARENDRA

    2008-03-01

    Full Text Available The present investigation concerns the evaluation of the effect of formulation variables on in vitro floating time and the release properties in developing a floating drug delivery system (FDDS containing a highly water soluble drug metoprolol tartrate (MT in the presence of a gas generating agent. A 32 full factorial design was employed in formulating the FDDS containing hydroxyl propylmethylcellulose (HPMC K4M and sodium carboxymethylcellulose (NaCMC as swellable polymers. Drug-to-polymer ratio and polymer-to-polymer ratio were included as independent variables. The main effect and the interaction terms were quantitatively evaluated by a quadratic model to predict formulations with the floating time desired, and the release properties. It was found that only drug-to-polymer ratio and its quadratic term were found to be significantly affective for all the response variables. Non-Fickian transport was confirmed as a release mechanism from the optimized formulations. The desirability function was used to optimize the response variables, each having a different target, and the observed responses were highly agreed with experimental values. The results demonstrate the feasibility of the model in the development of FDDS containing a highly water-soluble drug MT.

  8. Pharmacokinetics of IDX184, a liver-targeted oral prodrug of 2'-methylguanosine-5'-monophosphate, in the monkey and formulation optimization for human exposure.

    Pan-Zhou, Xin-Ru; Mayes, Benjamin A; Rashidzadeh, Hassan; Gasparac, Rahela; Smith, Steven; Bhadresa, Sanjeev; Gupta, Kusum; Cohen, Marita Larsson; Bu, Charlie; Good, Steven S; Moussa, Adel; Rush, Roger

    2016-10-01

    IDX184 is a phosphoramidate prodrug of 2'-methylguanosine-5'-monophosphate, developed to treat patients infected with hepatitis C virus. A mass balance study of radiolabeled IDX184 and pharmacokinetic studies of IDX184 in portal vein-cannulated monkeys revealed relatively low IDX184 absorption but higher exposure of IDX184 in the portal vein than in the systemic circulation, indicating >90 % of the absorbed dose was subject to hepatic extraction. Systemic exposures to the main metabolite, 2'-methylguanosine (2'-MeG), were used as a surrogate for liver levels of the pharmacologically active entity 2'-MeG triphosphate, and accordingly, systemic levels of 2'-MeG in the monkey were used to optimize formulations for further clinical development of IDX184. Capsule formulations of IDX184 delivered acceptable levels of 2'-MeG in humans; however, the encapsulation process introduced low levels of the genotoxic impurity ethylene sulfide (ES), which necessitated formulation optimization. Animal pharmacokinetic data guided the development of a tablet with trace levels of ES and pharmacokinetic performance equal to that of the clinical capsule in the monkey. Under fed conditions in humans, the new tablet formulation showed similar exposure to the capsule used in prior clinical trials.

  9. Optimizing the co-feeding strategy of Persian sturgeon (Acipenser persicus larvae using Artemia nauplii and formulated diet

    Naser Agh

    2013-07-01

    Full Text Available High mortality and labor costs are associated with first-feeding sturgeon culture, particularly during the period of dietary transition from live to formulated feed. Therefore we investigated the effects of various feeding treatments on the survival and growth of the Persian sturgeon (Acipenser persicus larvae during a 20-day culture period. Three replicate groups (250 fish/replicate of first-feeding larvae were fed according to four main feeding regimes: (1 live food (live nauplii of brine shrimp Artemia urmiana; (2 indirect transition (5 days live food followed by gradual transition to formulated diet; (3 direct transition (using different combinations of live and formulated diet from the start feeding onwards; (4 formulated feed (FD from the start feeding. Results indicated that growth and survival were higher in the indirect transition feeding regime than in other regimes. Based on our study, co-feeding of A. persicus should start five days after prior feeding with live food.

  10. Constrained consequence

    Britz, K

    2011-09-01

    Full Text Available their basic properties and relationship. In Section 3 we present a modal instance of these constructions which also illustrates with an example how to reason abductively with constrained entailment in a causal or action oriented context. In Section 4 we... of models with the former approach, whereas in Section 3.3 we give an example illustrating ways in which C can be de ned with both. Here we employ the following versions of local consequence: De nition 3.4. Given a model M = hW;R;Vi and formulas...

  11. Need for denser geodetic network to get real constrain on the fault behavior along the Main Marmara Sea segments of the NAF, toward an optimized GPS network.

    Klein, E.; Masson, F.; Duputel, Z.; Yavasoglu, H.; Agram, P. S.

    2016-12-01

    Over the last two decades, the densification of GPS networks and the development of new radar satellites offered an unprecedented opportunity to study crustal deformation due to faulting. Yet, submarine strike slip fault segments remain a major issue, especially when the landscape appears unfavorable to the use of SAR measurements. It is the case of the North Anatolian fault segments located in the Main Marmara Sea, that remain unbroken ever since the Mw7.4 earthquake of Izmit in 1999, which ended a eastward migrating seismic sequence of Mw > 7 earthquakes. Located directly offshore Istanbul, evaluation of seismic hazard appears capital. But a strong controversy remains over whether these segments are accumulating strain and are likely to experience a major earthquake, or are creeping, resulting both from the simplicity of current geodetic models and the scarcity of geodetic data. We indeed show that 2D infinite fault models cannot account for the complexity of the Marmara fault segments. But current geodetic data in the western region of Istanbul are also insufficient to invert for the coupling using a 3D geometry of the fault. Therefore, we implement a global optimization procedure aiming at identifying the most favorable distribution of GPS stations to explore the strain accumulation. We present here the results of this procedure that allows to determine both the optimal number and location of the new stations. We show that a denser terrestrial survey network can indeed locally improve the resolution on the shallower part of the fault, even more efficiently with permanent stations. But data closer from the fault, only possible by submarine measurements, remain necessary to properly constrain the fault behavior and its potential along strike coupling variations.

  12. Use of constrained mixture design for optimization of method for determination of zinc and manganese in tea leaves employing slurry sampling

    Almeida Bezerra, Marcos, E-mail: mbezerra47@yahoo.com.br [Universidade Estadual do Sudoeste da Bahia, Laboratorio de Quimica Analitica, 45200-190, Jequie, Bahia (Brazil); Teixeira Castro, Jacira [Universidade Federal do Reconcavo da Bahia, Centro de Ciencias Exatas e Tecnologicas, 44380-000, Cruz das Almas, Bahia (Brazil); Coelho Macedo, Reinaldo; Goncalves da Silva, Douglas [Universidade Estadual do Sudoeste da Bahia, Laboratorio de Quimica Analitica, 45200-190, Jequie, Bahia (Brazil)

    2010-06-18

    A slurry suspension sampling technique has been developed for manganese and zinc determination in tea leaves by using flame atomic absorption spectrometry. The proportions of liquid-phase of the slurries composed by HCl, HNO{sub 3} and Triton X-100 solutions have been optimized applying a constrained mixture design. The optimized conditions were 200 mg of sample ground in a tungsten carbide balls mill (particle size < 100 {mu}m), dilution in a liquid-phase composed by 2.0 mol L{sup -1} nitric, 2.0 mol L{sup -1} hydrochloric acid and 2.5% Triton X-100 solutions (in the proportions of 50%, 12% and 38% respectively), sonication time of 10 min and final slurry volume of 50.0 mL. This method allowed the determination of manganese and zinc by FAAS, with detection limits of 0.46 and 0.66 {mu}g g{sup -1}, respectively. The precisions, expressed as relative standard deviation (RSD), are 6.9 and 5.5% (n = 10), for concentrations of manganese and zinc of 20 and 40 {mu}g g{sup -1}, respectively. The accuracy of the method was confirmed by analysis of the certified apple leaves (NIST 1515) and spinach leaves (NIST 1570a). The proposed method was applied for the determination of manganese and zinc in tea leaves used for the preparation of infusions. The obtained concentrations varied between 42 and 118 {mu}g g{sup -1} and 18.6 and 90 {mu}g g{sup -1}, respectively, for manganese and zinc. The results were compared with those obtained by an acid digestion procedure and determination of the elements by FAAS. There was no significant difference between the results obtained by the two methods based on a paired t-test (at 95% confidence level).

  13. Mathematical Modeling of Constrained Hamiltonian Systems

    Schaft, A.J. van der; Maschke, B.M.

    1995-01-01

    Network modelling of unconstrained energy conserving physical systems leads to an intrinsic generalized Hamiltonian formulation of the dynamics. Constrained energy conserving physical systems are directly modelled as implicit Hamiltonian systems with regard to a generalized Dirac structure on the

  14. A comprehensive linear programming tool to optimize formulations of ready-to-use therapeutic foods: an application to Ethiopia.

    Ryan, Kelsey N; Adams, Katherine P; Vosti, Stephen A; Ordiz, M Isabel; Cimo, Elizabeth D; Manary, Mark J

    2014-12-01

    Ready-to-use therapeutic food (RUTF) is the standard of care for children suffering from noncomplicated severe acute malnutrition (SAM). The objective was to develop a comprehensive linear programming (LP) tool to create novel RUTF formulations for Ethiopia. A systematic approach that surveyed international and national crop and animal food databases was used to create a global and local candidate ingredient database. The database included information about each ingredient regarding nutrient composition, ingredient category, regional availability, and food safety, processing, and price. An LP tool was then designed to compose novel RUTF formulations. For the example case of Ethiopia, the objective was to minimize the ingredient cost of RUTF; the decision variables were ingredient weights and the extent of use of locally available ingredients, and the constraints were nutritional and product-quality related. Of the new RUTF formulations found by the LP tool for Ethiopia, 32 were predicted to be feasible for creating a paste, and these were prepared in the laboratory. Palatable final formulations contained a variety of ingredients, including fish, different dairy powders, and various seeds, grains, and legumes. Nearly all of the macronutrient values calculated by the LP tool differed by <10% from results produced by laboratory analyses, but the LP tool consistently underestimated total energy. The LP tool can be used to develop new RUTF formulations that make more use of locally available ingredients. This tool has the potential to lead to production of a variety of low-cost RUTF formulations that meet international standards and thereby potentially allow more children to be treated for SAM. © 2014 American Society for Nutrition.

  15. Formulation development and optimization of sustained release matrix tablet of Itopride HCl by response surface methodology and its evaluation of release kinetics.

    Bose, Anirbandeep; Wong, Tin Wui; Singh, Navjot

    2013-04-01

    The objective of this present investigation was to develop and formulate sustained release (SR) matrix tablets of Itopride HCl, by using different polymer combinations and fillers, to optimize by Central Composite Design response surface methodology for different drug release variables and to evaluate drug release pattern of the optimized product. Sustained release matrix tablets of various combinations were prepared with cellulose-based polymers: hydroxy propyl methyl cellulose (HPMC) and polyvinyl pyrolidine (pvp) and lactose as fillers. Study of pre-compression and post-compression parameters facilitated the screening of a formulation with best characteristics that underwent here optimization study by response surface methodology (Central Composite Design). The optimized tablet was further subjected to scanning electron microscopy to reveal its release pattern. The in vitro study revealed that combining of HPMC K100M (24.65 MG) with pvp(20 mg)and use of LACTOSE as filler sustained the action more than 12 h. The developed sustained release matrix tablet of improved efficacy can perform therapeutically better than a conventional tablet.

  16. Canonical Duality Theory for Topology Optimization

    Gao, David Yang

    2016-01-01

    This paper presents a canonical duality approach for solving a general topology optimization problem of nonlinear elastic structures. By using finite element method, this most challenging problem can be formulated as a mixed integer nonlinear programming problem (MINLP), i.e. for a given deformation, the first-level optimization is a typical linear constrained 0-1 programming problem, while for a given structure, the second-level optimization is a general nonlinear continuous minimization pro...

  17. A comprehensive linear programming tool to optimize formulations of ready-to-use therapeutic foods: An application to Ethiopia

    Ready-to-use therapeutic food (RUTF) is the standard of care for children suffering from noncomplicated severe acute malnutrition (SAM). The objective was to develop a comprehensive linear programming (LP) tool to create novel RUTF formulations for Ethiopia. A systematic approach that surveyed inter...

  18. Sustained ocular delivery of Dorzolamide-HCl via proniosomal gel formulation: in-vitro characterization, statistical optimization, and in-vivo pharmacodynamic evaluation in rabbits.

    Fouda, Nagwa Hussein; Abdelrehim, Randa Tag; Hegazy, Doaa Abdelmagid; Habib, Basant Ahmed

    2018-11-01

    Glaucoma is the second cause of blindness worldwide. Frequent administration of traditional topical dosage forms may lead to patient incompliance and failure of treatment. Our study aims to formulate proniosomal gel formulations that sustain the release of the water-soluble anti-glaucoma drug Dorzolamide-HCl (Dorz). Proniosomal gel formulations were prepared using coacervation phase separation method according to a 5 2 full factorial design. The effects of Cholesterol and surfactant (Span 40) amounts (independent variables) on the percentage entrapment efficiency (EE%), particle size (PS), and the percent of drug released after 8 h (Q8h) (dependent variables (DVs)) were investigated. An optimized formulation (OF) was chosen based on maximizing EE% and Q8h and minimizing PS. An intraocular pressure (IOP) pharmacodynamic study was performed in rabbits to evaluate the in-vivo performance of the OF-gel compared to the marketed Trusopt ® eye drops. The results showed that the independent variables studied significantly affected EE%, PS, and Q8h. OF was the one containing 60 mg Cholesterol and 540 mg Span 40. It had desirability of 0.885 and its actually measured DVs deviated from the predicted ones by a maximum of 4.8%. The in-vivo pharmacodynamic study showed that OF could result in higher reduction in IOP, significantly sustain that reduction in IOP and increase Dorz bioavailability compared to Trusopt ® eye drops. Thus the OF-gel is very promising for being used in glaucoma treatment.

  19. Solid self-nanoemulsifying drug delivery systems for oral delivery of polypeptide-k: Formulation, optimization, in-vitro and in-vivo antidiabetic evaluation.

    Garg, Varun; Kaur, Puneet; Singh, Sachin Kumar; Kumar, Bimlesh; Bawa, Palak; Gulati, Monica; Yadav, Ankit Kumar

    2017-11-15

    Development of self-nanoemulsifying drug delivery systems (SNEDDS) of polypeptide-k (PPK) is reported with the aim to achieve its oral delivery. Box-Behnken design (BBD) was adopted to develop and optimize the composition of SNEDDS. Oleoyl polyoxyl-6 glycerides (A), Tween 80 (B), and diethylene glycol monoethyl ether (C) were used as oil, surfactant and co-surfactant, respectively as independent variables. The effect of variation in their composition was observed on the mean droplet size (y1), polydispersity index (PDI) (y2), % drug loading (y3) and zeta potential (y4). As per the optimal design, seventeen SNEDDS prototypes were prepared. The optimized composition of SNEDDS formulation was 25% v/v Oleoyl polyoxyl-6 glycerides, 37% v/v Tween 80, 38% v/v diethylene glycol monoethyl ether, and 3% w/v PPK. The optimized formulation revealed values of y1, y2, y3, and y4 as 31.89nm, 0.16, 73.15%, and -15.65mV, respectively. Further the optimized liquid SNEDDS were solidified through spray drying using various hydrophilic and hydrophobic carriers. Among the various carriers, Aerosil 200 was found to provide desirable flow, compression, disintegration and dissolution properties. Both, liquid and solid-SNEDDS have shown release of >90% within 10min. The formulation was found stable with change in pH, dilution, temperature variation and freeze thaw cycles in terms of droplet size, zeta potential, drug precipitation and phase separation. Crystalline PPK was observed in amorphous state in solid SNEDDS when characterized through DSC and PXRD studies. The biochemical, hematological and histopathological results of streptozotocin induced diabetic rats shown promising antidiabetic potential of PPK loaded in SNEDDS at its both the doses (i.e. 400mg/kg and 800mg/kg) as compared to its naïve form at both the doses. The study revealed successful formulation of SNEDDS for oral delivery of PPK. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. A CLASS OF NONMONOTONE TRUST REGION ALGORITHMS FOR LINEARLY CONSTRAINED OPTIMIZATION%线性约束优化的一类非单调信赖域算法

    葛恒武; 陈中文

    2002-01-01

    We present a class of nonmonotone trust region algorithms for linearly constrained optimization in this paper.The algorithm may adjust automatically the scope of the monotonicity by the degree that the quadratic model is "trusted".Under the suitable conditions,it is proved that any limit point of the infinite sequence generated by the algorithm is the Kuhn-Tucker point of the primal problem.Finally,some numerical results show that the new algorithm is very effective.

  1. Formulation and optimization of pH sensitive drug releasing O/W emulsions using Albizia lebbeck L. seed polysaccharide.

    Varma, Chekuri Ashok Kumar; Jayaram Kumar, K

    2018-04-30

    Smart polymers, one of the class of polymers with extensive growth in the last few decades due to their wide applications in drug targeting and controlled delivery systems. With this in mind, the aim of the present study is to design and formulate smart releasing o/w emulsion by using Albizia lebbeck L. seed polysaccharide (ALPS). For this purpose, the physicochemical and drug release characteristics like emulsion capacity (EC), emulsion stability (ES), viscosity, microscopy, zeta potential, polydispersity index (PDI) and in-vitro drug release were performed. The EC and ES values were found to increase with an increased concentration of ALPS. The emulsion formulations were statistically designed by using 3 2 full factorial design. All the emulsions showed a shear-thinning behavior. The zeta potential and polydispersity index were found to be in the range of -35.83 mV to -19.00 mV and 0.232-1.000 respectively. Further, the percent cumulative drug release of the emulsions at 8 h was found to be in the range of 30.19-82.65%. The drug release profile exhibited zero order release kinetics. In conclusion, the ALPS can be used as a natural emulsifier and smart polymer for the preparation of pH sensitive emulsions in drug delivery systems. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Optimization and physicochemical characterization of a cationic lipid-phosphatidylcholine mixed emulsion formulated as a highly efficient vehicle that facilitates adenoviral gene transfer

    Kim SY

    2017-10-01

    Full Text Available Soo-Yeon Kim,1,2 Sang-Jin Lee,2 Jin-Ki Kim,3 Han-Gon Choi,3 Soo-Jeong Lim1 1Department of Bioscience and Bioengineering, Sejong University, Seoul, Kwangjin-gu, Seoul, 2Immunotherapeutics Branch, Research Institute, National Cancer Center, Ilsandong-gu, Goyang-si, Gyeonggi-do, 3College of Pharmacy & Institute of Pharmaceutical Science and Technology, Hanyang University, Sangnok-gu, Ansan, Republic of Korea Abstract: Cationic lipid-based nanoparticles enhance viral gene transfer by forming electrostatic complexes with adenoviral vectors. We recently demonstrated the superior complexation capabilities of 1,2-dioleoyl-3-trimethylammonium propane (DOTAP emulsion compared with a liposomal counterpart but the cytotoxicity of DOTAP emulsions remained a challenge. The present study is aimed at formulating an emulsion capable of acting as a highly effective viral gene transfer vehicle with reduced cytotoxicity and to physicochemically characterize the structures of virus-emulsion complexes in comparison with virus–liposome complexes when the only difference between emulsions and liposomes was the presence or absence of inner oil core. The emulsion formulation was performed by 1 reducing the content of DOTAP while increasing the content of zwitterionic lipid 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC, and 2 optimizing the oil content. The complexation capability of formulated DOTAP:DMPC mixed emulsions was similar to those of emulsions containing DOTAP alone while displaying significantly lower cytotoxicity. The complexation capabilities of the DOTAP:DMPC mixed emulsion were serum-compatible and were monitored in a variety of cell types, whereas its liposomal counterpart was totally ineffective. Characterization by scanning electron microscopy, transmission electron microscopy, atomic force microscopy, and dynamic light scattering studies indicated that the optimized emulsions spontaneously surrounded the virus particles to generate emulsions that

  3. Study on Formulation Optimization of Black Soybean Paste%黑豆沙配方优化研究

    杨益叶; 周宏胜; 胡花丽; 罗淑芬; 李鹏霞

    2018-01-01

    Black soybean variety "Xindali No. 1" was taken as the raw material of black soybean paste processing, and the optimum formulation of black soybean paste preparation was studied. The sensory quality score of product was used as the evalua-tion criterion. Firstly, sunflower seed oil and white granulated sugar were selected as the best species of oil and sugar for the pro-cessing of black soybean paste. Secondly, the ranges of optimum addition amount of flour, sunflower seed oil and white granulated sugar in black soybean paste were determined based on the results of single-factor tests. Finally, the best proportion of flour, sun-flower seed oil and white granulated sugar in black soybean paste was ascertained through the orthogonal test. The optimum formu-lation of black soybean paste preparation was obtained as follows:50 g black soybean, 20 g white granulated sugar, 15 g sunflow-er seed oil, and 20 g flour. The prepared black soybean paste through the above best formulation had fine and smooth taste, uni-form color and lustre, and unique fragrance without obvious oil leaking out.%针对黑豆沙加工工艺缺乏的现状,以新大粒1号黑豆为原料,进行黑豆沙加工过程主要添加物的配方优化研究.以感官品质评分为标准,首先确定了加工过程中所需的油与糖的最优种类为葵花籽油和白砂糖;基于单因素试验确定面粉、葵花籽油、白砂糖的最佳用量范围,再通过正交试验的方法确定面粉、葵花籽油、白砂糖的最优配比.最终确定新大粒1号黑豆沙最佳配方为:以黑豆质量为基准(100%),添加40%白砂糖,30%葵花籽油,40%面粉.通过该配方制得的黑豆沙口感细腻,色泽均匀,无明显走油现象,具有黑豆沙独特的香味和色泽.

  4. Lithium-ion battery capacity fading dynamics modelling for formulation optimization: A stochastic approach to accelerate the design process

    Tao, Laifa; Cheng, Yujie; Lu, Chen; Su, Yuzhuan; Chong, Jin; Jin, Haizu; Lin, Yongshou; Noktehdan, Azadeh

    2017-01-01

    Highlights: •The model is linked to known physicochemical degradation processes and material properties. •Aging dynamics of various battery formulations can be understood by the proposed model. •Large number of experiments will be reduced to accelerate the battery design process. •This approach can describe batteries under various operating conditions. •The proposed model is simple and easily implemented. -- Abstract: A five-state nonhomogeneous Markov chain model, which is an effective and promising way to accelerate the Li-ion battery design process by investigating the capacity fading dynamics of different formulations during the battery design phase, is reported. The parameters of this model are linked to known physicochemical degradation dynamics and material properties. Herein, the states and behaviors of the active materials in Li-ion batteries are modelled. To verify the efficiency of the proposed model, a dataset from approximately 3 years of cycling capacity fading experiments of various formulations using several different materials provided by Contemporary Amperex Technology Limited (CATL), as well as a NASA dataset, are employed. The capabilities of the proposed model for different amounts (50%, 70%, and 90%) of available experimental capacity data are tested and analyzed to assist with the final design determination for manufacturers. The average relative errors of life cycling prediction acquired from these tests are less than 2.4%, 0.8%, and 0.3%, even when only 50%, 70%, and 90% of the data, respectively, is available for different anode materials, electrolyte materials, and individual batteries. Furthermore, the variance is 0.518% when only 50% of the data are available; i.e., one can save at least 50% of the total experimental time and cost with an accuracy greater than 97% in the design phase, which demonstrates an effective and promising way to accelerate the Li-ion battery design process. The qualitative and quantitative analyses

  5. Probabilistic Constrained Load Flow Considering Integration of Wind Power Generation and Electric Vehicles

    Vlachogiannis, Ioannis (John)

    2009-01-01

    A new formulation and solution of probabilistic constrained load flow (PCLF) problem suitable for modern power systems with wind power generation and electric vehicles (EV) demand or supply is represented. The developed stochastic model of EV demand/supply and the wind power generation model...... are incorporated into load flow studies. In the resulted PCLF formulation, discrete and continuous control parameters are engaged. Therefore, a hybrid learning automata system (HLAS) is developed to find the optimal offline control settings over a whole planning period of power system. The process of HLAS...

  6. Formulation and optimization of doxorubicin loaded polymeric nanoparticles using Box-Behnken design: ex-vivo stability and in-vitro activity.

    Shaikh, Muhammad Vaseem; Kala, Manika; Nivsarkar, Manish

    2017-03-30

    Biodegradable nanoparticles (NPs) have gained tremendous interest for targeting chemotherapeutic drugs to the tumor environment. Inspite of several advances sufficient encapsulation along with the controlled release and desired size range have remained as considerable challenges. Hence, the present study examines the formulation optimization of doxorubicin loaded PLGA NPs (DOX-PLGA-NPs), prepared by single emulsion method for cancer targeting. Critical process parameters (CPP) were selected by initial screening. Later, Box-Behnken design (BBD) was used for analyzing the effect of the selected CPP on critical quality attributes (CQA) and to generate a design space. The optimized formulation was stabilized by lyophilization and was used for in-vitro drug release and in-vitro activity on A549 cell line. Moreover, colloidal stability of the NPs in the biological milieu was assessed. Amount of PLGA and PVA, oil:water ratio and sonication time were the selected independent factors for BBD. The statistical data showed that a quadratic model was fitted to the data obtained. Additionally, the lack of fit values for the models was not significant. The delivery system showed sustained release behavior over a period of 120h and was governed by Fickian diffusion. The multipoint analysis at 24, 48 and 72h showed gradual reduction in IC50 value of DOX-PLGA-NPs (p<0.05, Fig. 9). DOX-PLGA-NPs were found to be stable in the biological fluids indicating their in-vivo applicability. In conclusion, optimization of the DOX-PLGA-NPs by BBD yielded in a promising drug carrier for doxorubicin that could provide a novel treatment modality for cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Optimization of operation for combined heat and power plants - CHP plants - with heat accumulators using a MILP formulation

    Grue, Jeppe; Bach, Inger [Aalborg Univ. (Denmark). Inst. of Energy Technology]. E-mails: jeg@iet.auc.dk; ib@iet.auc.dk

    2000-07-01

    The power generation system in Denmark is extensively based on small combined heat and power plants (CHP plants), producing both electricity and district heating. This project deals with smaller plants spread throughout the country. Often a heat accumulator is used to enable electricity production, even when the heat demand is low. This system forms a very complex problem, both for sizing, designing and operation of CHP plants. The objective of the work is the development of a tool for optimisation of the operation of CHP plants, and to even considering the design of the plant. The problem is formulated as a MILP-problem. An actual case is being tested, involving CHP producing units to cover the demand. The results from this project show that it is of major importance to consider the operation of the plant in detail already in the design phase. It is of major importance to consider the optimisation of the plant operation, even at the design stage, as it may cause the contribution margin to rise significantly, if the plant is designed on the basis of a de-tailed knowledge of the expected operation. (author)

  8. Revising the retrieval technique of a long-term stratospheric HNO{sub 3} data set. From a constrained matrix inversion to the optimal estimation algorithm

    Fiorucci, I.; Muscari, G. [Istituto Nazionale di Geofisica e Vulcanologia, Rome (Italy); De Zafra, R.L. [State Univ. of New York, Stony Brook, NY (United States). Dept. of Physics and Astronomy

    2011-07-01

    The Ground-Based Millimeter-wave Spectrometer (GBMS) was designed and built at the State University of New York at Stony Brook in the early 1990s and since then has carried out many measurement campaigns of stratospheric O{sub 3}, HNO{sub 3}, CO and N{sub 2}O at polar and mid-latitudes. Its HNO{sub 3} data set shed light on HNO{sub 3} annual cycles over the Antarctic continent and contributed to the validation of both generations of the satellite-based JPL Microwave Limb Sounder (MLS). Following the increasing need for long-term data sets of stratospheric constituents, we resolved to establish a long-term GMBS observation site at the Arctic station of Thule (76.5 N, 68.8 W), Greenland, beginning in January 2009, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Furthermore, we updated the retrieval algorithm adapting the Optimal Estimation (OE) method to GBMS spectral data in order to conform to the standard of the Network for the Detection of Atmospheric Composition Change (NDACC) microwave group, and to provide our retrievals with a set of averaging kernels that allow more straightforward comparisons with other data sets. The new OE algorithm was applied to GBMS HNO{sub 3} data sets from 1993 South Pole observations to date, in order to produce HNO{sub 3} version 2 (v2) profiles. A sample of results obtained at Antarctic latitudes in fall and winter and at mid-latitudes is shown here. In most conditions, v2 inversions show a sensitivity (i.e., sum of column elements of the averaging kernel matrix) of 100{+-}20% from 20 to 45 km altitude, with somewhat worse (better) sensitivity in the Antarctic winter lower (upper) stratosphere. The 1{sigma} uncertainty on HNO{sub 3} v2 mixing ratio vertical profiles depends on altitude and is estimated at {proportional_to}15% or 0.3 ppbv, whichever is larger. Comparisons of v2 with former (v1) GBMS HNO{sub 3} vertical profiles

  9. Formulation and demonstration of a robust mean variance optimization approach for concurrent airline network and aircraft design

    Davendralingam, Navindran

    Conceptual design of aircraft and the airline network (routes) on which aircraft fly on are inextricably linked to passenger driven demand. Many factors influence passenger demand for various Origin-Destination (O-D) city pairs including demographics, geographic location, seasonality, socio-economic factors and naturally, the operations of directly competing airlines. The expansion of airline operations involves the identificaion of appropriate aircraft to meet projected future demand. The decisions made in incorporating and subsequently allocating these new aircraft to serve air travel demand affects the inherent risk and profit potential as predicted through the airline revenue management systems. Competition between airlines then translates to latent passenger observations of the routes served between OD pairs and ticket pricing---this in effect reflexively drives future states of demand. This thesis addresses the integrated nature of aircraft design, airline operations and passenger demand, in order to maximize future expected profits as new aircraft are brought into service. The goal of this research is to develop an approach that utilizes aircraft design, airline network design and passenger demand as a unified framework to provide better integrated design solutions in order to maximize expexted profits of an airline. This is investigated through two approaches. The first is a static model that poses the concurrent engineering paradigm above as an investment portfolio problem. Modern financial portfolio optimization techniques are used to leverage risk of serving future projected demand using a 'yet to be introduced' aircraft against potentially generated future profits. Robust optimization methodologies are incorporated to mitigate model sensitivity and address estimation risks associated with such optimization techniques. The second extends the portfolio approach to include dynamic effects of an airline's operations. A dynamic programming approach is

  10. Efficacy of very fast simulated annealing global optimization method for interpretation of self-potential anomaly by different forward formulation over 2D inclined sheet type structure

    Biswas, A.; Sharma, S. P.

    2012-12-01

    Self-Potential anomaly is an important geophysical technique that measures the electrical potential due natural source of current in the Earth's subsurface. An inclined sheet type model is a very familiar structure associated with mineralization, fault plane, groundwater flow and many other geological features which exhibits self potential anomaly. A number of linearized and global inversion approaches have been developed for the interpretation of SP anomaly over different structures for various purposes. Mathematical expression to compute the forward response over a two-dimensional dipping sheet type structures can be described in three different ways using five variables in each case. Complexities in the inversion using three different forward approaches are different. Interpretation of self-potential anomaly using very fast simulated annealing global optimization has been developed in the present study which yielded a new insight about the uncertainty and equivalence in model parameters. Interpretation of the measured data yields the location of the causative body, depth to the top, extension, dip and quality of the causative body. In the present study, a comparative performance of three different forward approaches in the interpretation of self-potential anomaly is performed to assess the efficacy of the each approach in resolving the possible ambiguity. Even though each forward formulation yields the same forward response but optimization of different sets of variable using different forward problems poses different kinds of ambiguity in the interpretation. Performance of the three approaches in optimization has been compared and it is observed that out of three methods, one approach is best and suitable for this kind of study. Our VFSA approach has been tested on synthetic, noisy and field data for three different methods to show the efficacy and suitability of the best method. It is important to use the forward problem in the optimization that yields the

  11. The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

    Denis Pinha

    2016-11-01

    Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

  12. An integrated, quality by design (QbD) approach for design, development and optimization of orally disintegrating tablet formulation of carbamazepine.

    Mishra, Saurabh M; Rohera, Bhagwan D

    2017-11-01

    The objective of the present study was to design and develop a formulation for orally disintegrating tablets (ODTs) of carbamazepine using quality by design principles. The target product profile (TPP) and quality target product profile (QTPP) of ODTs were identified. Risk assessment was carried out by leveraging prior knowledge and experience to define the criticality of factors based on their impact by Ishikawa fishbone diagram and preliminary hazard analysis tool. Box-Behnken response surface methodology was used to study the effect of critical factors on various attributes of ODTs. The independent factors selected were compression pressure (X 1 ), concentration of sublimating agent (volatile material) (X 2 ), disintegrant concentration (X 3 ) and the responses were tablet crushing strength, tablet porosity, disintegration time, water absorption time, tablet friability and drug dissolution. ANOVA and lack of fit test illustrated that selected independent variables had significant effect on the response variables, and excellent correlation was observed between actual and predicted values. Optimization by desirability function indicated that compression pressure, X 1 (1534 lbs), ammonium bicarbonate concentration, X 2 (7.68%) and Kollidon ® CL-SF concentration, X 3 (6%) were optimum to prepare ODT formulation of carbamazepine of desired attributes complying with QTPP. Thus, in the present study, a high level of assurance was established for ODT product quality and performance.

  13. The Challenge of Peat Substitution in Organic Seedling Production: Optimization of Growing Media Formulation through Mixture Design and Response Surface Analysis.

    Francesco Giovanni Ceglie

    Full Text Available Peat replacement is an increasing demand in containerized and transplant production, due to the environmental constraints associated to peat use. However, despite the wide information concerning the use of alternative materials as substrates, it is very complex to establish the best materials and mixtures. This work evaluates the use of mixture design and surface response methodology in a peat substitution experiment using two alternative materials (green compost and palm fibre trunk waste for transplant production of tomato (Lycopersicon esculentum Mill.; melon, (Cucumis melo L.; and lettuce (Lactuca sativa L. in organic farming conditions. In general, the substrates showed suitable properties for their use in seedling production, showing the best plant response the mixture of 20% green compost, 39% palm fibre and 31% peat. The mixture design and applied response surface methodology has shown to be an useful approach to optimize substrate formulations in peat substitution experiments to standardize plant responses.

  14. Aceclofenac nanocrystals with enhanced in vitro, in vivo performance: formulation optimization, characterization, analgesic and acute toxicity studies

    Rahim H

    2017-08-01

    .65% and its marketed tablets (17.65%. The in vivo studies of the produced stabilized nanosuspension demonstrated that the Cmax were 4.98- and 2.80-fold while area under curve from time of administration to 24 h (AUC0→24 h were found 3.88- and 2.10-fold greater when compared with unprocessed drug and its marketed formulation, respectively. The improved antinociceptive activity of AC nanocrystals was shown at much lower doses as compared to unprocessed drug, which is purely because of nanonization which may be attributed to improved solubility and dissolution rate of AC, ultimately resulting in its faster rate of absorption. Keywords: aceclofenac nanocrystals, precipitation–ultrasonication, dissolution rate, in vivo studies

  15. Formulation and optimization of a novel oral fast dissolving film containing drug nanoparticles by Box-Behnken design-response surface methodology.

    Shen, Chengying; Shen, Baode; Xu, He; Bai, Jinxia; Dai, Ling; Lv, Qingyuan; Han, Jin; Yuan, Hailong

    2014-05-01

    The purpose of this study was to design and optimize a novel drug nanoparticles-loaded oral fast dissolving film (NP-OFDF) using Box-Behnken design-response surface methodology. Drug nanosuspensions produced from high pressure homogenization were transformed into oral fast dissolving film containing drug nanoparticles by casting methods. Herpetrione (HPE), a novel and potent antiviral agent with poor water solubility that was extracted from Herpetospermum caudigerum, was studied as the model drug. The formulations of oral fast dissolving film containing HPE nanoparticles (HPE-NP-OFDF) were optimized by employing Box-Behnken design-response surface methodology and then systematically characterized. The optimized HPE-NP-OFDF was disintegrated in water within 20 s with reconstituted nanosuspensions particle size of 299.31 nm. Scanning electron microscopy (SEM) images showed that well-dispersed HPE nanoparticles with slight adhesion to each other were exposed on the surface of film or embedded in film. The X-ray diffractogram (XRD) analysis suggested that HPE in the HPE-NP-OFDF was in the amorphous state. In-vitro release study, approximate 77.23% of HPE was released from the HPE-NP-OFDF within 5 min, which was more than eight times compared with that of HPE raw materials (9.57%). The optimized HPE-NP-OFDF exhibits much faster drug release rates compared to HPE raw material, which indicated that this novel NP-OFDF may provide a potential opportunity for oral delivery of drugs with poor water solubility.

  16. Mesh dependence in PDE-constrained optimisation an application in tidal turbine array layouts

    Schwedes, Tobias; Funke, Simon W; Piggott, Matthew D

    2017-01-01

    This book provides an introduction to PDE-constrained optimisation using finite elements and the adjoint approach. The practical impact of the mathematical insights presented here are demonstrated using the realistic scenario of the optimal placement of marine power turbines, thereby illustrating the real-world relevance of best-practice Hilbert space aware approaches to PDE-constrained optimisation problems. Many optimisation problems that arise in a real-world context are constrained by partial differential equations (PDEs). That is, the system whose configuration is to be optimised follows physical laws given by PDEs. This book describes general Hilbert space formulations of optimisation algorithms, thereby facilitating optimisations whose controls are functions of space. It demonstrates the importance of methods that respect the Hilbert space structure of the problem by analysing the mathematical drawbacks of failing to do so. The approaches considered are illustrated using the optimisation problem arisin...

  17. Chemometrical aspects of quality in pharmaceutical technology : the application of robustness criteria and multi criteria decision making in optimization procedures for pharmaceutical formulations

    Boer, Jan Hendrik de

    1992-01-01

    In pharmaceutical technology one is often engaged with the design and analysis of formulations. A formulation of a solid dosage form is normally a mixture of components. This formulation usually consists of a number of components with fixed concentrations like the the medicinal substance(s) (drug),

  18. Minimum Time Trajectory Optimization of CNC Machining with Tracking Error Constraints

    Qiang Zhang

    2014-01-01

    Full Text Available An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

  19. Multi-objective optimization strategy based on desirability functions used for electrophoratic separation and quantification of rosiglitazone and glimepiride in plasma and formulations.

    Hefnawy, Mohamed M; Sultan, Maha A; Al-Johar, Haya I; Kassem, Mohamed G; Aboul-Enein, Hassan Y

    2012-01-01

    Multiple response simultaneous optimization employing Derringer's desirability function was used for the development of a capillary electrophoresis method for the simultaneous determination of rosiglitazone (RSG) and glimepiride (GLM) in plasma and formulations. Twenty experiments, taking the two resolutions, the analysis time, and the capillary current as the responses with three important factors--buffer morality, volte and column temperature--were used to design mathematical models. The experimental responses were fitted into a second order polynomial and the six responses were simultaneously optimized to predict the optimum conditions for the effective separation of the studied compounds. The separation was carried out by using capillary zone electrophoresis (CZE) with a silica capillary column and diode array detector at 210 nm. The optimum assay conditions were 52 mmol l⁻¹ phosphate buffer, pH 7, and voltage of 22 kV at 29 °C. The method showed good agreement between the experimental data and predictive value throughout the studied parameter space. The assay limit of detection was 0.02 µg ml⁻¹ and the effective working range at relative standard deviation (RSD) of ≤ 5% was 0.05-16 µg ml⁻¹ (r = 0.999) for both drugs. Analytical recoveries of the studied drugs from spiked plasma were 97.2-101.9 ± 0.31-3.0%. The precision of the assay was satisfactory; RSD was 1.07 and 1.14 for intra- and inter-assay precision, respectively. The proposed method has a great value in routine analysis of RSG and GLM for its therapeutic monitoring and pharmacokinetic studies. Copyright © 2011 John Wiley & Sons, Ltd.

  20. An experimental design approach for optimization of spectrophotometric method for estimation of cefixime trihydrate using ninhydrin as derivatizing reagent in bulk and pharmaceutical formulation

    Yogita B. Wani

    2017-01-01

    Full Text Available The aim of the present work is to use experimental design to screen and optimize experimental variables for developing a spectrophotometric method for determining cefixime trihydrate content using ninhydrin as a derivatizing reagent. The method is based on the reaction of the amino group of cefixime with ninhydrin in an alkaline medium to form a yellow-colored derivative (λmax 436 nm. A two-level full factorial design was utilized to screen the effect of ninhydrin reagent concentration (X1, volume of ninhydrin reagent (X2, heating temperature (X3 and heating time (X4 on the formation of the cefixime–ninhydrin complex Y (absorbance. One way ANOVA and Pareto ranking analyses have shown that the ninhydrin reagent concentration (X1, volume of ninhydrin reagent (X2 and heating temperature (X3 were statistically significant factors (P < 0.05 affecting the formation of the cefixime–ninhydrin complex Y (absorbance. A Box-Behnken experimental design with response surface methodology was then utilized to evaluate the main, interaction and quadratic effects of these three factors on the selected response. With the help of a response surface plot and contour plot the optimum values of the selected factors were determined and used for further experiments. These values were a ninhydrin reagent concentration (X1 of 0.2% w/v, volume of ninhydrin reagent (X2 of 1 mL and heating temperature (X3 of 80 °C. The proposed method was validated according to the ICH Q2 (R1 method validation guidelines. The results of the present study have clearly shown that an experimental design concept may be effectively applied to the optimization of a spectrophotometric method for estimating the cefixime trihydrate content in bulk and pharmaceutical formulation with the least number of experimental runs possible.

  1. Recent advances in computational optimization

    2013-01-01

    Optimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency. Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization. This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc...

  2. Formulation and optimization of niosomes for topical diacerein delivery using 3-factor, 3-level Box-Behnken design for the management of psoriasis.

    Moghddam, Seyedeh Raziyeh Mahdavi; Ahad, Abdul; Aqil, Mohd; Imam, Syed Sarim; Sultana, Yasmin

    2016-12-01

    This research aimed towards the design of preparations of diacerein loaded cholesterol rich niosomes by employing a 3-factor, 3-level Box-Behnken design. Results indicated that Span 60 (90mg) and cholesterol (10mg), and 45min of hydration time were found to be optimum for niosomes preparation. The prepared cholesterol rich niosomes were uniform and spherical in size. Optimized formulation F2 entrapped the drug with 83.02% efficiency in the cholesterol rich niosomes of the size 477.8nm, presented the flux of 2.820μg/cm(2)/h, followed Higuchi model and non Fickian transport mechanism. The confocal laser scanning microscopy showed that niosomes accentuated the penetration of diacerein in the epidermal and dermal layer of rat skin. Stability study confirmed that cholesterol rich niosomes were stable for 2months at 4°C. Concisely, the results showed that targeted diacerein delivery might be achieved using topically applied niosomes for enhanced treatment of psoriasis, which might eliminate adverse side effects associated with systemic exposure. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Constrained Null Space Component Analysis for Semiblind Source Separation Problem.

    Hwang, Wen-Liang; Lu, Keng-Shih; Ho, Jinn

    2018-02-01

    The blind source separation (BSS) problem extracts unknown sources from observations of their unknown mixtures. A current trend in BSS is the semiblind approach, which incorporates prior information on sources or how the sources are mixed. The constrained independent component analysis (ICA) approach has been studied to impose constraints on the famous ICA framework. We introduced an alternative approach based on the null space component (NCA) framework and referred to the approach as the c-NCA approach. We also presented the c-NCA algorithm that uses signal-dependent semidefinite operators, which is a bilinear mapping, as signatures for operator design in the c-NCA approach. Theoretically, we showed that the source estimation of the c-NCA algorithm converges with a convergence rate dependent on the decay of the sequence, obtained by applying the estimated operators on corresponding sources. The c-NCA can be formulated as a deterministic constrained optimization method, and thus, it can take advantage of solvers developed in optimization society for solving the BSS problem. As examples, we demonstrated electroencephalogram interference rejection problems can be solved by the c-NCA with proximal splitting algorithms by incorporating a sparsity-enforcing separation model and considering the case when reference signals are available.

  4. Energy-efficient relay selection and optimal power allocation for performance-constrained dual-hop variable-gain AF relaying

    Zafar, Ammar

    2013-12-01

    This paper investigates the energy-efficiency enhancement of a variable-gain dual-hop amplify-and-forward (AF) relay network utilizing selective relaying. The objective is to minimize the total consumed power while keeping the end-to-end signal-to-noise-ratio (SNR) above a certain peak value and satisfying the peak power constraints at the source and relay nodes. To achieve this objective, an optimal relay selection and power allocation strategy is derived by solving the power minimization problem. Numerical results show that the derived optimal strategy enhances the energy-efficiency as compared to a benchmark scheme in which both the source and the selected relay transmit at peak power. © 2013 IEEE.

  5. Energy efficient LED layout optimization for near-uniform illumination

    Ali, Ramy E.; Elgala, Hany

    2016-09-01

    In this paper, we consider the problem of designing energy efficient light emitting diodes (LEDs) layout while satisfying the illumination constraints. Towards this objective, we present a simple approach to the illumination design problem based on the concept of the virtual LED. We formulate a constrained optimization problem for minimizing the power consumption while maintaining a near-uniform illumination throughout the room. By solving the resulting constrained linear program, we obtain the number of required LEDs and the optimal output luminous intensities that achieve the desired illumination constraints.

  6. A Sequential Quadratically Constrained Quadratic Programming Method of Feasible Directions

    Jian Jinbao; Hu Qingjie; Tang Chunming; Zheng Haiyan

    2007-01-01

    In this paper, a sequential quadratically constrained quadratic programming method of feasible directions is proposed for the optimization problems with nonlinear inequality constraints. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving only one subproblem which consist of a convex quadratic objective function and simple quadratic inequality constraints without the second derivatives of the functions of the discussed problems, and such a subproblem can be formulated as a second-order cone programming which can be solved by interior point methods. To overcome the Maratos effect, an efficient higher-order correction direction is obtained by only one explicit computation formula. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions without the strict complementarity. Finally, some preliminary numerical results are reported

  7. Assessment of oscillatory stability constrained available transfer capability

    Jain, T.; Singh, S.N.; Srivastava, S.C.

    2009-01-01

    This paper utilizes a bifurcation approach to compute oscillatory stability constrained available transfer capability (ATC) in an electricity market having bilateral as well as multilateral transactions. Oscillatory instability in non-linear systems can be related to Hopf bifurcation. At the Hopf bifurcation, one pair of the critical eigenvalues of the system Jacobian reaches imaginary axis. A new optimization formulation, including Hopf bifurcation conditions, has been developed in this paper to obtain the dynamic ATC. An oscillatory stability based contingency screening index, which takes into account the impact of transactions on severity of contingency, has been utilized to identify critical contingencies to be considered in determining ATC. The proposed method has been applied for dynamic ATC determination on a 39-bus New England system and a practical 75-bus Indian system considering composite static load as well as dynamic load models. (author)

  8. The preparation of Cistanche phenylethanoid glycosides liquid proliposomes: Optimized formulation, characterization and proliposome dripping pills in vitro and in vivo evaluation.

    Li, Meng; Li, Yunjing; Liu, Weiwei; Li, Rongli; Qin, Cuiying; Liu, Nan; Han, Jing

    2016-10-10

    Water-soluble Cistanche phenylethanoid glycosides (CPhGs) have poor permeability and low bioavailability. However, liposomes can improve the permeability of such drugs and their poor stability, and proliposomes have been used to overcome these problems. Based on this, Cistanche phenylethanoid glycoside liquid proliposomes (CPhGsP) and dripping(?) pills were prepared and optimized using response surface methodology. The properties of CPhGsP were evaluated in terms of their encapsulation efficiency, particle size, zeta potential, and morphology. The results obtained showed that the optimal formulation was drug/soybean phospholipid/poloxamer-188/sodium deoxycholate/propylene glycol 1:22.38:3.52:0.84:80 (w/w/w/w/v). This resulted in an encapsulation efficiency, particle size, and zeta potential of hydrated proliposomes with phosphate buffer solution (pH7.4) of 51.97%, 671.7nm, and -25.49mV, respectively. Stability testing of CPhGsP and CPhGs ordinary liposomes was carried out for 3months at 4±2°C, 25±2°C, 40±2°C, 75±5% RH. The results obtained showed that the stability of the proliposomes was better than that of ordinary liposomes at the same temperature, while a lower temperature of 4°C is ideal for storage. Cistanche phenylethanoid glycoside liquid proliposomes dripping pills (CPhGsPD) are efficiently released in gastrointestinal solution as shown by in vitro release experiments and the structure of the liposomes does not destroy the proliposome dripping pills by hydration. In vivo experiments showed that the areas under the plasma level-time curves and peak concentrations of CPhGsPD and hydrated proliposomes were higher than those of CPhGs. Moreover, with CPhGsPD, the pharmacokinetic parameters were similar to those with hydrated proliposomes. These results showed that CPhGsPD offer a good way to improve the oral delivery of CPhGs. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Automated beam steering using optimal control

    Allen, C. K. (Christopher K.)

    2004-01-01

    We present a steering algorithm which, with the aid of a model, allows the user to specify beam behavior throughout a beamline, rather than just at specified beam position monitor (BPM) locations. The model is used primarily to compute the values of the beam phase vectors from BPM measurements, and to define cost functions that describe the steering objectives. The steering problem is formulated as constrained optimization problem; however, by applying optimal control theory we can reduce it to an unconstrained optimization whose dimension is the number of control signals.

  10. Chance-constrained programming approach to natural-gas curtailment decisions

    Guldmann, J M

    1981-10-01

    This paper presents a modeling methodology for the determination of optimal-curtailment decisions by a gas-distribution utility during a chronic gas-shortage situation. Based on the end-use priority approach, a linear-programming model is formulated, that reallocates the available gas supply among the utility's customers while minimizing fuel switching, unemployment, and utility operating costs. This model is then transformed into a chance-constrained program in order to account for the weather-related variability of the gas requirements. The methodology is applied to the East Ohio Gas Company. 16 references, 2 figures, 3 tables.

  11. Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

    Ling Lu

    2016-12-01

    Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

  12. Application of the EGM Method to a LED-Based Spotlight: A Constrained Pseudo-Optimization Design Process Based on the Analysis of the Local Entropy Generation Maps

    Enrico Sciubba

    2011-06-01

    Full Text Available In this paper, the entropy generation minimization (EGM method is applied to an industrial heat transfer problem: the forced convective cooling of a LED-based spotlight. The design specification calls for eighteen diodes arranged on a circular copper plate of 35 mm diameter. Every diode dissipates 3 W and the maximum allowedtemperature of the plate is 80 °C. The cooling relies on the forced convection driven by a jet of air impinging on the plate. An initial complex geometry of plate fins is presented and analyzed with a commercial CFD code that computes the entropy generation rate. A pseudo-optimization process is carried out via a successive series of design modifications based on a careful analysis of the entropy generation maps. One of the advantages of the EGM method is that the rationale behind each step of the design process can be justified on a physical basis. It is found that the best performance is attained when the fins are periodically spaced in the radial direction.

  13. Baseline LAW Glass Formulation Testing

    Kruger, Albert A.; Mooers, Cavin; Bazemore, Gina; Pegg, Ian L.; Hight, Kenneth; Lai, Shan Tao; Buechele, Andrew; Rielley, Elizabeth; Gan, Hao; Muller, Isabelle S.; Cecil, Richard

    2013-01-01

    The major objective of the baseline glass formulation work was to develop and select glass formulations that are compliant with contractual and processing requirements for each of the LAW waste streams. Other objectives of the work included preparation and characterization of glasses with respect to the properties of interest, optimization of sulfate loading in the glasses, evaluation of ability to achieve waste loading limits, testing to demonstrate compatibility of glass melts with melter materials of construction, development of glass formulations to support ILAW qualification activities, and identification of glass formulation issues with respect to contract specifications and processing requirements

  14. Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis.

    Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe

    2013-04-01

    Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.

  15. A chance-constrained stochastic approach to intermodal container routing problems.

    Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

    2018-01-01

    We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

  16. Application of pattern search method to power system security constrained economic dispatch with non-smooth cost function

    Al-Othman, A.K.; El-Naggar, K.M.

    2008-01-01

    Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED) with non-smooth cost function. Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using three different test systems. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED). In addition, valve-point effect loading and total system losses are considered to further investigate the potential of the PS technique. Based on the results, it can be concluded that the PS has demonstrated ability in handling highly nonlinear discontinuous non-smooth cost function of the SCED. (author)

  17. Closedness type regularity conditions in convex optimization and beyond

    Sorin-Mihai Grad

    2016-09-01

    Full Text Available The closedness type regularity conditions have proven during the last decade to be viable alternatives to their more restrictive interiority type counterparts, in both convex optimization and different areas where it was successfully applied. In this review article we de- and reconstruct some closedness type regularity conditions formulated by means of epigraphs and subdifferentials, respectively, for general optimization problems in order to stress that they arise naturally when dealing with such problems. The results are then specialized for constrained and unconstrained convex optimization problems. We also hint towards other classes of optimization problems where closedness type regularity conditions were successfully employed and discuss other possible applications of them.

  18. Single Layer Extended Release Two-in-One Guaifenesin Matrix Tablet: Formulation Method, Optimization, Release Kinetics Evaluation and Its Comparison with Mucinex® Using Box-Behnken Design.

    Morovati, Amirhosein; Ghaffari, Alireza; Erfani Jabarian, Lale; Mehramizi, Ali

    2017-01-01

    Guaifenesin, a highly water-soluble active (50 mg/mL), classified as a BCS class I drug. Owing to its poor flowability and compressibility, formulating tablets especially high-dose one, may be a challenge. Direct compression may not be feasible. Bilayer tablet technology applied to Mucinex®, endures challenges to deliver a robust formulation. To overcome challenges involved in bilayer-tablet manufacturing and powder compressibility, an optimized single layer tablet prepared by a binary mixture (Two-in-one), mimicking the dual drug release character of Mucinex ® was purposed. A 3-factor, 3-level Box-Behnken design was applied to optimize seven considered dependent variables (Release "%" in 1, 2, 4, 6, 8, 10 and 12 h) regarding different levels of independent one (X 1 : Cetyl alcohol, X 2 : Starch 1500 ® , X 3 : HPMC K100M amounts). Two granule portions were prepared using melt and wet granulations, blended together prior to compression. An optimum formulation was obtained (X 1 : 37.10, X 2 : 2, X 3 : 42.49 mg). Desirability function was 0.616. F2 and f1 between release profiles of Mucinex® and the optimum formulation were 74 and 3, respectively. An n-value of about 0.5 for both optimum and Mucinex® formulations showed diffusion (Fickian) control mechanism. However, HPMC K100M rise in 70 mg accompanied cetyl alcohol rise in 60 mg led to first order kinetic (n = 0.6962). The K values of 1.56 represented an identical burst drug releases. Cetyl alcohol and starch 1500 ® modulated guaifenesin release from HPMC K100M matrices, while due to their binding properties, improved its poor flowability and compressibility, too.

  19. Optimization of the new formulation of ice cream with native Iranian seed gums (Lepidium perfoliatum and Lepidium sativum) using response surface methodology (RSM).

    Azari-Anpar, M; Soltani Tehrani, N; Aghajani, N; Khomeiri, M

    2017-01-01

    In this study, effect of Qodume shahri ( Lepidium perfoliatum ) and cress ( Lepidium sativum ) on rheological properties of ice cream were investigated. The gums were added to the ice cream formulation and different quality attributes including pH, acidity, melting characteristics, viscosity, overrun, texture analysis and sensory evaluation were determined. Results showed that ice cream formulations containing both the gums had improved overrun, melting rate, first dripping time, viscosity, hardness and adhesiveness. The gum concentrations beyond 0.2% level led to a negative effect on gumminess and chewiness of ice cream. Both the gums addition to improved quality attributes and textural properties of ice cream.

  20. Performance Evaluation of Abrasive Grinding Wheel Formulated ...

    This paper presents a study on the formulation and manufacture of abrasive grinding wheel using locally formulated silicon carbide abrasive grains. Six local raw material substitutes were identified through pilot study and with the initial mix of the identified materials, a systematic search for an optimal formulation of silicon ...

  1. Statistical mechanics of budget-constrained auctions

    Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.

    2009-01-01

    Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). Based on the cavity method of statistical mechanics, we introduce a message passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution,...

  2. Development and optimization of a new processing approach for manufacturing topical liposomes-in-hydrogel drug formulations by dual asymmetric centrifugation.

    Ingebrigtsen, Sveinung G; Škalko-Basnet, Nataša; Holsæter, Ann Mari

    2016-09-01

    The objective of the present study was to utilize dual asymmetric centrifugation (DAC) as a novel processing approach for the production of liposomes-in-hydrogel formulations. Lipid films of phosphatidylcholine, with and without chloramphenicol (CAM), were hydrated and homogenized by DAC to produce liposomes in the form of vesicular phospholipid gels with a diameter in the size range of 200-300 nm suitable for drug delivery to the skin. Different homogenization processing parameters were investigated along with the effect of adding propylene glycol (PG) to the formulations prior to homogenization. The produced liposomes were incorporated into a hydrogel made of 2.5% (v/v) soluble β-1,3/1,6-glucan (SBG) and mixed by DAC to achieve a homogenous liposomes-in-hydrogel-formulation suitable for topical application. CAM-containing liposomes with a vesicle diameter of 282 ± 30 nm and polydispersity index (PI) of 0.13 ± 0.02 were successfully produced by DAC after 50 min centrifugation at 3500 rpm, and homogenously (< 4% content variation) incorporated into the SBG hydrogel. Addition of PG decreased the necessary centrifugation time to 2 min and 55 s, producing liposomes of 230 ± 51 nm and PI of 0.25 ± 0.04. All formulations had an entrapment efficiency of approximately 50%. We managed to develop a relatively fast and reproducible new method for the production of liposomes-in-hydrogel formulations by DAC.

  3. Constraint Optimization for Highly Constrained Logistic Problems

    Mochnacs, Maria Kinga; Tanaka, Meang Akira; Nyborg, Anders

    This report investigates whether propagators combined with branch and bound algorithm are suitable for solving the storage area stowage problem within reasonable time. The approach has not been attempted before and experiments show that the implementation was not capable of solving the storage ar...

  4. Exploring Constrained Creative Communication

    Sørensen, Jannick Kirk

    2017-01-01

    Creative collaboration via online tools offers a less ‘media rich’ exchange of information between participants than face-to-face collaboration. The participants’ freedom to communicate is restricted in means of communication, and rectified in terms of possibilities offered in the interface. How do...... these constrains influence the creative process and the outcome? In order to isolate the communication problem from the interface- and technology problem, we examine via a design game the creative communication on an open-ended task in a highly constrained setting, a design game. Via an experiment the relation...... between communicative constrains and participants’ perception of dialogue and creativity is examined. Four batches of students preparing for forming semester project groups were conducted and documented. Students were asked to create an unspecified object without any exchange of communication except...

  5. Choosing health, constrained choices.

    Chee Khoon Chan

    2009-12-01

    In parallel with the neo-liberal retrenchment of the welfarist state, an increasing emphasis on the responsibility of individuals in managing their own affairs and their well-being has been evident. In the health arena for instance, this was a major theme permeating the UK government's White Paper Choosing Health: Making Healthy Choices Easier (2004), which appealed to an ethos of autonomy and self-actualization through activity and consumption which merited esteem. As a counterpoint to this growing trend of informed responsibilization, constrained choices (constrained agency) provides a useful framework for a judicious balance and sense of proportion between an individual behavioural focus and a focus on societal, systemic, and structural determinants of health and well-being. Constrained choices is also a conceptual bridge between responsibilization and population health which could be further developed within an integrative biosocial perspective one might refer to as the social ecology of health and disease.

  6. Optimally Stopped Optimization

    Vinci, Walter; Lidar, Daniel

    We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known, and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time, optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark the performance of a D-Wave 2X quantum annealer and the HFS solver, a specialized classical heuristic algorithm designed for low tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N = 1098 variables, the D-Wave device is between one to two orders of magnitude faster than the HFS solver.

  7. Learning optimal embedded cascades.

    Saberian, Mohammad Javad; Vasconcelos, Nuno

    2012-10-01

    The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and optimization of individual cascade stages, so as to achieve the best tradeoff between classification accuracy and speed, under a detection rate constraint. Two novel boosting algorithms are proposed to address these problems. The first, RCBoost, formulates boosting as a constrained optimization problem which is solved with a barrier penalty method. The constraint is the target detection rate, which is met at all iterations of the boosting process. This enables the design of embedded cascades of known configuration without extensive cross validation or heuristics. The second, ECBoost, searches over cascade configurations to achieve the optimal tradeoff between classification risk and speed. The two algorithms are combined into an overall boosting procedure, RCECBoost, which optimizes both the cascade configuration and its stages under a detection rate constraint, in a fully automated manner. Extensive experiments in face, car, pedestrian, and panda detection show that the resulting detectors achieve an accuracy versus speed tradeoff superior to those of previous methods.

  8. Constrained superfields in supergravity

    Dall’Agata, Gianguido; Farakos, Fotis [Dipartimento di Fisica ed Astronomia “Galileo Galilei”, Università di Padova,Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova,Via Marzolo 8, 35131 Padova (Italy)

    2016-02-16

    We analyze constrained superfields in supergravity. We investigate the consistency and solve all known constraints, presenting a new class that may have interesting applications in the construction of inflationary models. We provide the superspace Lagrangians for minimal supergravity models based on them and write the corresponding theories in component form using a simplifying gauge for the goldstino couplings.

  9. Minimal constrained supergravity

    Cribiori, N. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Dall' Agata, G., E-mail: dallagat@pd.infn.it [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Farakos, F. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Porrati, M. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

    2017-01-10

    We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

  10. Minimal constrained supergravity

    N. Cribiori

    2017-01-01

    Full Text Available We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

  11. Minimal constrained supergravity

    Cribiori, N.; Dall'Agata, G.; Farakos, F.; Porrati, M.

    2017-01-01

    We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

  12. A Continuous Formulation for Logical Decisions in Differential Algebraic Systems using Mathematical Programs with Complementarity Constraints

    Kody M. Powell

    2016-03-01

    Full Text Available This work presents a methodology to represent logical decisions in differential algebraic equation simulation and constrained optimization problems using a set of continuous algebraic equations. The formulations may be used when state variables trigger a change in process dynamics, and introduces a pseudo-binary decision variable, which is continuous, but should only have valid solutions at values of either zero or one within a finite time horizon. This formulation enables dynamic optimization problems with logical disjunctions to be solved by simultaneous solution methods without using methods such as mixed integer programming. Several case studies are given to illustrate the value of this methodology including nonlinear model predictive control of a chemical reactor using a surge tank with overflow to buffer disturbances in feed flow rate. Although this work contains novel methodologies for solving dynamic algebraic equation (DAE constrained problems where the system may experience an abrupt change in dynamics that may otherwise require a conditional statement, there remain substantial limitations to this methodology, including a limited domain where problems may converge and the possibility for ill-conditioning. Although the problems presented use only continuous algebraic equations, the formulation has inherent non-smoothness. Hence, these problems must be solved with care and only in select circumstances, such as in simulation or situations when the solution is expected to be near the solver’s initial point.

  13. Resource Management in Constrained Dynamic Situations

    Seok, Jinwoo

    Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments

  14. Optimal shutdown management

    Bottasso, C L; Croce, A; Riboldi, C E D

    2014-01-01

    The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way

  15. Optimal shutdown management

    Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.

    2014-06-01

    The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.

  16. Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

    Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

    2012-01-01

    Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

  17. Non Linear Programming (NLP formulation for quantitative modeling of protein signal transduction pathways.

    Alexander Mitsos

    Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

  18. Systematic Approach for the Formulation and Optimization of Solid Lipid Nanoparticles of Efavirenz by High Pressure Homogenization Using Design of Experiments for Brain Targeting and Enhanced Bioavailability

    Gupta, Shweta; Kesarla, Rajesh; Chotai, Narendra; Misra, Ambikanandan

    2017-01-01

    The nonnucleoside reverse transcriptase inhibitors, used for the treatment of HIV infections, are reported to have low bioavailability pertaining to high first-pass metabolism, high protein binding, and enzymatic metabolism. They also show low permeability across blood brain barrier. The CNS is reported to be the most important HIV reservoir site. In the present study, solid lipid nanoparticles of efavirenz were prepared with the objective of providing increased permeability and protection of drug due to biocompatible lipidic content and nanoscale size and thus developing formulation having potential for enhanced bioavailability and brain targeting. Solid lipid nanoparticles were prepared by high pressure homogenization technique using a systematic approach of design of experiments (DoE) and evaluated for particle size, polydispersity index, zeta potential, and entrapment efficiency. Particles of average size 108.5 nm having PDI of 0.172 with 64.9% entrapment efficiency were produced. Zeta potential was found to be −21.2 mV and the formulation was found stable. The in-vivo pharmacokinetic studies revealed increased concentration of the drug in brain, as desired, when administered through intranasal route indicating its potential for an attempt towards complete eradication of HIV and cure of HIV-infected patients. PMID:28243600

  19. Use of a screening method to determine excipients which optimize the extent and stability of supersaturated drug solutions and application of this system to solid formulation design.

    Vandecruys, Roger; Peeters, Jef; Verreck, Geert; Brewster, Marcus E

    2007-09-05

    Assessing the effect of excipients on the ability to attain and maintain supersaturation of drug-based solution may provide useful information for the design of solid formulations. Judicious selection of materials that affect either the extent or stability of supersaturating drug delivery systems may be enabling for poorly soluble drug candidates or other difficult-to-formulate compounds. The technique suggested herein is aimed at providing a screening protocol to allow preliminary assessment of these factors based on small to moderate amounts of drug substance. A series of excipients were selected that may, by various mechanisms, affect supersaturation including pharmaceutical polymers such as HMPC and PVP, surfactants such as Polysorbate 20, Cremophor RH40 and TPGS and hydrophilic cyclodextrins such as HPbetaCD. Using a co-solvent based method and 25 drug candidates, the data suggested, on the whole, that the surfactants and the selected cyclodextrin seemed to best augment the extent of supersaturation but had variable benefits as stabilizers, while the pharmaceutical polymers had useful effect on supersaturation stability but were less helpful in increasing the extent of supersaturation. Using these data, a group of simple solid dosage forms were prepared and tested in the dog for one of the drug candidates. Excipients that gave the best extent and stability for the formed supersaturated solution in the screening assay also gave the highest oral bioavailability in the dog.

  20. Constrained Vapor Bubble Experiment

    Gokhale, Shripad; Plawsky, Joel; Wayner, Peter C., Jr.; Zheng, Ling; Wang, Ying-Xi

    2002-11-01

    Microgravity experiments on the Constrained Vapor Bubble Heat Exchanger, CVB, are being developed for the International Space Station. In particular, we present results of a precursory experimental and theoretical study of the vertical Constrained Vapor Bubble in the Earth's environment. A novel non-isothermal experimental setup was designed and built to study the transport processes in an ethanol/quartz vertical CVB system. Temperature profiles were measured using an in situ PC (personal computer)-based LabView data acquisition system via thermocouples. Film thickness profiles were measured using interferometry. A theoretical model was developed to predict the curvature profile of the stable film in the evaporator. The concept of the total amount of evaporation, which can be obtained directly by integrating the experimental temperature profile, was introduced. Experimentally measured curvature profiles are in good agreement with modeling results. For microgravity conditions, an analytical expression, which reveals an inherent relation between temperature and curvature profiles, was derived.