MINIMUM DISCRIMINATION INFORMATION PROBLEMS VIA GENERALIZED GEOMETRIC PROGRAMMING
Institute of Scientific and Technical Information of China (English)
ZhuDetong
2003-01-01
In this paper,the quadratic program problm and minimum discrimiation in formation (MDI) problem with a set of quadratic inequality constraints and entropy constraints of density are considered.Based on the properties of the generalized geometric programming,the dual programs of thses two problems are derived.Furthermore,the duality theorms and related Kuhn-Tucker conditions for two pairs of the prime-dual programs are also established by the duality theory.
Geometric Programming Approach to an Interactive Fuzzy Inventory Problem
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Nirmal Kumar Mandal
2011-01-01
Full Text Available An interactive multiobjective fuzzy inventory problem with two resource constraints is presented in this paper. The cost parameters and index parameters, the storage space, the budgetary cost, and the objective and constraint goals are imprecise in nature. These parameters and objective goals are quantified by linear/nonlinear membership functions. A compromise solution is obtained by geometric programming method. If the decision maker is not satisfied with this result, he/she may try to update the current solution to his/her satisfactory solution. In this way we implement man-machine interactive procedure to solve the problem through geometric programming method.
Geometric Programming Problem with Co-Efficients and Exponents Associated with Binary Numbers
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A. K. Das
2010-01-01
Full Text Available Geometric programming (GP provides a power tool for solving a variety of optimization problems. In the real world, many applications of geometric programming (GP are engineering design problems in which some of the problem parameters are estimating of actual values. This paper develops a solution procedure to solve nonlinear programming problems using GP technique by splitting the cost coefficients, constraint coefficients and exponents with the help of binary numbers. The equivalent mathematical programming problems are formulated to find their corresponding value of the objective function based on the duality theorem. The ability of calculating the cost coefficients, constraint coefficients and exponents developed in this paper might help lead to more realistic modeling efforts in engineering design areas. Standard nonlinear programming software has been used to solve the proposed optimization problem. Two numerical examples are presented to illustrate the method.
Localized Geometric Query Problems
Augustine, John; Maheshwari, Anil; Nandy, Subhas C; Roy, Sasanka; Sarvattomananda, Swami
2011-01-01
A new class of geometric query problems are studied in this paper. We are required to preprocess a set of geometric objects $P$ in the plane, so that for any arbitrary query point $q$, the largest circle that contains $q$ but does not contain any member of $P$, can be reported efficiently. The geometric sets that we consider are point sets and boundaries of simple polygons.
Solving a class of geometric programming problems by an efficient dynamic model
Nazemi, Alireza; Sharifi, Elahe
2013-03-01
In this paper, a neural network model is constructed on the basis of the duality theory, optimization theory, convex analysis theory, Lyapunov stability theory and LaSalle invariance principle to solve geometric programming (GP) problems. The main idea is to convert the GP problem into an equivalent convex optimization problem. A neural network model is then constructed for solving the obtained convex programming problem. By employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the original problem. The simulation results also show that the proposed neural network is feasible and efficient.
Multi-item fuzzy inventory problem with space constraint via geometric programming method
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Mandal Kumar Nirmal
2006-01-01
Full Text Available In this paper, a multi-item inventory model with space constraint is developed in both crisp and fuzzy environment. A profit maximization inventory model is proposed here to determine the optimal values of demands and order levels of a product. Selling price and unit price are assumed to be demand-dependent and holding and set-up costs sock dependent. Total profit and warehouse space are considered to be vague and imprecise. The impreciseness in the above objective and constraint goals has been expressed by fuzzy linear membership functions. The problem is then solved using modified geometric programming method. Sensitivity analysis is also presented here.
A multi objective geometric programming approach for electronic product pricing problem
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Mohsen Fathollah Bayati
2011-07-01
Full Text Available Nowadays electronic commerce plays an important role in many business activities, operations, and transaction processing. The recent advances on e-businesses have created tremendous opportunities to increase profitability. This paper presents a multi-objective marketing planning model which simultaneously determines efficient marketing expenditure, service cost and product's selling price in two competitive markets. To solve the proposed model, we discuss a multi-objective geometric programming (GP approach based on compromise programming method. Since our proposed model is a signomial GP and global optimality is not guaranteed for the problem, we transform the model to posynomial form. Finally, the solution procedure is illustrated via a numerical example and a sensitivity analysis is presented.
Mahavira's Geometrical Problems
DEFF Research Database (Denmark)
Høyrup, Jens
2004-01-01
Analysis of the geometrical chapters Mahavira's 9th-century Ganita-sara-sangraha reveals inspiration from several chronological levels of Near-Eastern and Mediterranean mathematics: (1)that known from Old Babylonian tablets, c. 1800-1600 BCE; (2)a Late Babylonian but pre-Seleucid Stratum, probably...
Study on the Grey Polynomial Geometric Programming
Institute of Scientific and Technical Information of China (English)
LUODang
2005-01-01
In the model of geometric programming, values of parameters cannot be gotten owing to data fluctuation and incompletion. But reasonable bounds of these parameters can be attained. This is to say, parameters of this model can be regarded as interval grey numbers. When the model contains grey numbers, it is hard for common programming method to solve them. By combining the common programming model with the grey system theory,and using some analysis strategies, a model of grey polynomial geometric programming, a model of 8 positioned geometric programming and their quasi-optimum solution or optimum solution are put forward. At the same time, we also developed an algorithm for the problem.This approach brings a new way for the application research of geometric programming. An example at the end of this paper shows the rationality and feasibility of the algorithm.
MM Algorithms for Geometric and Signomial Programming.
Lange, Kenneth; Zhou, Hua
2014-02-01
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
The Geometric Gravitational Internal Problem
González-Martin, G R
2000-01-01
In a geometric unified theory there is an energy momentum equation, apart from the field equations and equations of motion. The general relativity Einstein equation with cosmological constant follows from this energy momentum equation for empty space. For non empty space we obtain a generalized Einstein equation, relating the Einstein tensor to a geometric stress energy tensor. The matching exterior solution is in agreement with the standard relativity tests. Furthermore, there is a Newtonian limit where we obtain Poisson's equation.
Geometric weighting method for solving multi-objective programming problems%几何加权法求解多目标规划问题
Institute of Scientific and Technical Information of China (English)
乔辰; 张国立
2011-01-01
多目标规划的目标函数相互冲突,一般不存在最优解,因此求其非劣解具有重要意义.采用几何加权法提出了一种新的评价函数,通过这种评价函数将多目标规划的目标函数转化为单目标函数,并证明了该方法得到的最优解是多目标规划问题的非劣解.通过算例,比较了线性加权法,极大极小法,几何加权法.结果表明,几何加权法是可行的；通过几何加权法能够得到原问题的非劣解,而且当权重变化时,几何加权法的结果比线性加权法更符合实际.%The objective functions of multi-objective programming are conflict, there is generally has no optimized solution , so how to get its non-inferior solutions is of great importance. Using geometric weighting method proposed a new evaluation function, with this evaluation function can turn the multi-objective programming to the single objective programming, and It has proved that the solution obtained on geometric weighting method is non-inferior solution on multi-objective programming. Comparing three methods, that the linear weighting method, min-max method and the geometric weighting method, through an example. The results show that geometric weighting method is feasible and using geometric weighting method can obtain non-inferior solutions of the original problem, and when the weights change, the geometric weighting results more practical than the linear weighting method.
Microlocal Analysis of the Geometric Separation Problem
Donoho, David L
2010-01-01
Image data are often composed of two or more geometrically distinct constituents; in galaxy catalogs, for instance, one sees a mixture of pointlike structures (galaxy superclusters) and curvelike structures (filaments). It would be ideal to process a single image and extract two geometrically `pure' images, each one containing features from only one of the two geometric constituents. This seems to be a seriously underdetermined problem, but recent empirical work achieved highly persuasive separations. We present a theoretical analysis showing that accurate geometric separation of point and curve singularities can be achieved by minimizing the $\\ell_1$ norm of the representing coefficients in two geometrically complementary frames: wavelets and curvelets. Driving our analysis is a specific property of the ideal (but unachievable) representation where each content type is expanded in the frame best adapted to it. This ideal representation has the property that important coefficients are clustered geometrically ...
Institute of Scientific and Technical Information of China (English)
朱德通
2003-01-01
In this paper,the quadratic program problem and minimum discrimination information (MDI) problem with a set of quadratic inequality constraints and entropy constraints of density are considered.Based on the properties of the generalized geometric programming,the dual programs of these two problems are derived.Furthermore,the duality theorems and related Kuhn-Tucker conditions for two pairs of the prime-dual programs are also established by the duality theory.
Geometric problems in molecular biology and robotics.
Parsons, D; Canny, J
1994-01-01
Some of the geometric problems of interest to molecular biologists have macroscopic analogues in the field of robotics. Two examples of such analogies are those between protein docking and model-based perception, and between ring closure and inverse kinematics. Molecular dynamics simulation, too, has much in common with the study of robot dynamics. In this paper we give a brief survey of recent work on these and related problems.
Optimization of biotechnological systems through geometric programming
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Torres Nestor V
2007-09-01
Full Text Available Abstract Background In the past, tasks of model based yield optimization in metabolic engineering were either approached with stoichiometric models or with structured nonlinear models such as S-systems or linear-logarithmic representations. These models stand out among most others, because they allow the optimization task to be converted into a linear program, for which efficient solution methods are widely available. For pathway models not in one of these formats, an Indirect Optimization Method (IOM was developed where the original model is sequentially represented as an S-system model, optimized in this format with linear programming methods, reinterpreted in the initial model form, and further optimized as necessary. Results A new method is proposed for this task. We show here that the model format of a Generalized Mass Action (GMA system may be optimized very efficiently with techniques of geometric programming. We briefly review the basics of GMA systems and of geometric programming, demonstrate how the latter may be applied to the former, and illustrate the combined method with a didactic problem and two examples based on models of real systems. The first is a relatively small yet representative model of the anaerobic fermentation pathway in S. cerevisiae, while the second describes the dynamics of the tryptophan operon in E. coli. Both models have previously been used for benchmarking purposes, thus facilitating comparisons with the proposed new method. In these comparisons, the geometric programming method was found to be equal or better than the earlier methods in terms of successful identification of optima and efficiency. Conclusion GMA systems are of importance, because they contain stoichiometric, mass action and S-systems as special cases, along with many other models. Furthermore, it was previously shown that algebraic equivalence transformations of variables are sufficient to convert virtually any types of dynamical models into
Institute of Scientific and Technical Information of China (English)
朱德通
2002-01-01
A minimization problem of either a convex quadratic function or a minimum cross-entropy problem with a set of quadratical inequality constraints is considered.Based on the properties of the generalized geometric programming,the dual programs of two problems are derived.The duality theorems and related Kuhn-Tucker conditions for two pairs of the primal-dual programs are also established by using the duality theory.%研究带二次约束的最小二次规划和交互熵问题.基于广义几何规划的理论与性质,导出了上述两个规划原问题的对偶规划.进而,由广义几何规划的对偶理论建立了两个原始一对偶规划的对偶定理和Kuhn-Tucker条件.
A geometrical perspective for the bargaining problem.
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Kelvin Kian Loong Wong
Full Text Available A new treatment to determine the Pareto-optimal outcome for a non-zero-sum game is presented. An equilibrium point for any game is defined here as a set of strategy choices for the players, such that no change in the choice of any single player will increase the overall payoff of all the players. Determining equilibrium for multi-player games is a complex problem. An intuitive conceptual tool for reducing the complexity, via the idea of spatially representing strategy options in the bargaining problem is proposed. Based on this geometry, an equilibrium condition is established such that the product of their gains over what each receives is maximal. The geometrical analysis of a cooperative bargaining game provides an example for solving multi-player and non-zero-sum games efficiently.
A geometrical perspective for the bargaining problem.
Wong, Kelvin Kian Loong
2010-04-26
A new treatment to determine the Pareto-optimal outcome for a non-zero-sum game is presented. An equilibrium point for any game is defined here as a set of strategy choices for the players, such that no change in the choice of any single player will increase the overall payoff of all the players. Determining equilibrium for multi-player games is a complex problem. An intuitive conceptual tool for reducing the complexity, via the idea of spatially representing strategy options in the bargaining problem is proposed. Based on this geometry, an equilibrium condition is established such that the product of their gains over what each receives is maximal. The geometrical analysis of a cooperative bargaining game provides an example for solving multi-player and non-zero-sum games efficiently.
Geometric Error Analysis in Applied Calculus Problem Solving
Usman, Ahmed Ibrahim
2017-01-01
The paper investigates geometric errors students made as they tried to use their basic geometric knowledge in the solution of the Applied Calculus Optimization Problem (ACOP). Inaccuracies related to the drawing of geometric diagrams (visualization skills) and those associated with the application of basic differentiation concepts into ACOP…
Duals for classical inventory models via generalized geometric programming
Carlton H. Scott; Thomas R. Jefferson; Soheila Jorjani
2004-01-01
Inventory problems generally have a structure that can be exploited for computational purposes. Here, we look at the duals of two seemingly unrelated inventory models that suggest an interesting duality between discrete time optimal control and optimization over an ordered sequence of variables. Concepts from conjugate duality and generalized geometric programming are used to establish the duality.
Monomial geometric programming with an arbitrary fuzzy relational inequality
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E. Shivanian
2015-11-01
Full Text Available In this paper, an optimization model with geometric objective function is presented. Geometric programming is widely used; many objective functions in optimization problems can be analyzed by geometric programming. We often encounter these in resource allocation and structure optimization and technology management, etc. On the other hand, fuzzy relation equalities and inequalities are also used in many areas. We here present a geometric programming model with a monomial objective function subject to the fuzzy relation inequality constraints with an arbitrary function. The feasible solution set is determined and compared with some common results in the literature. A necessary and sufficient condition and three other necessary conditions are presented to conceptualize the feasibility of the problem. In general a lower bound is always attainable for the optimal objective value by removing the components having no effect on the solution process. By separating problem to non-decreasing and non-increasing function to prove the optimal solution, we simplify operations to accelerate the resolution of the problem.
Langlands Program, Trace Formulas, and their Geometrization
Frenkel, Edward
2012-01-01
The Langlands Program relates Galois representations and automorphic representations of reductive algebraic groups. The trace formula is a powerful tool in the study of this connection and the Langlands Functoriality Conjecture. After giving an introduction to the Langlands Program and its geometric version, which applies to curves over finite fields and over the complex field, I give a survey of my recent joint work with Robert Langlands and Ngo Bao Chau (arXiv:1003.4578 and arXiv:1004.5323) on a new approach to proving the Functoriality Conjecture using the trace formulas, and on the geometrization of the trace formulas. In particular, I discuss the connection of the latter to the categorification of the Langlands correspondence.
Quadratic 0-1 programming: Geometric methods and duality analysis
Liu, Chunli
The unconstraint quadratic binary problem (UBQP), as a classical combinatorial problem, finds wide applications in broad field and human activities including engineering, science, finance, etc. The NP-hardness of the combinatorial problems makes a great challenge to solve the ( UBQP). The main purpose of this research is to develop high performance solution method for solving (UBQP) via the geometric properties of the objective ellipse contour and the optimal solution. This research makes several contributions to advance the state-of-the-art of geometric approach of (UBQP). These contributions include both theoretical and numerical aspects as stated below. In part I of this dissertation, certain rich geometric properties hidden behind quadratic 0-1 programming are investigated. Especially, we derive new lower bounding methods and variable fixation techniques for quadratic 0-1 optimization problems by investigating geometric features of the ellipse contour of a (perturbed) convex quadratic function. These findings further lead to some new optimality conditions for quadratic 0-1 programming. Integrating these novel solution schemes into a proposed solution algorithm of a branch-and-bound type, we obtain promising preliminary computational results. In part II of this dissertation, we present new results of the duality gap between the binary quadratic optimization problem and its Lagrangian dual. We first derive a necessary and sufficient condition for the zero duality gap and discuss its relationship with the polynomial solvability of the problem. We then characterize the zeroness of duality gap by the distance, delta, between the binary set and certain affine space C. Finally, we discuss a computational procedure of the distance delta. These results provide new insights into the duality gap and polynomial solvability of binary quadratic optimization problems.
Brachytherapy seed localization using geometric and linear programming techniques.
Singh, Vikas; Mukherjee, Lopamudra; Xu, Jinhui; Hoffmann, Kenneth R; Dinu, Petru M; Podgorsak, Matthew
2007-09-01
We propose an optimization algorithm to solve the brachytherapy seed localization problem in prostate brachytherapy. Our algorithm is based on novel geometric approaches to exploit the special structure of the problem and relies on a number of key observations which help us formulate the optimization problem as a minimization integer program (IP). Our IP model precisely defines the feasibility polyhedron for this problem using a polynomial number of half-spaces; the solution to its corresponding linear program is rounded to yield an integral solution to our task of determining correspondences between seeds in multiple projection images. The algorithm is efficient in theory as well as in practice and performs well on simulation data (approximately 98% accuracy) and real X-ray images (approximately 95% accuracy). We present in detail the underlying ideas and an extensive set of performance evaluations based on our implementation.
Lower bounds for polynomials using geometric programming
Ghasemi, Mehdi
2011-01-01
We make use of a result of Hurwitz and Reznick, and a consequence of this result due to Fidalgo and Kovacec, to determine a new sufficient condition for a polynomial $f\\in\\mathbb{R}[X_1,...,X_n]$ of even degree to be a sum of squares. This result generalizes a result of Lasserre and a result of Fidalgo and Kovacec, and it also generalizes the improvements of these results given in [6]. We apply this result to obtain a new lower bound $f_{gp}$ for $f$, and we explain how $f_{gp}$ can be computed using geometric programming. The lower bound $f_{gp}$ is generally not as good as the lower bound $f_{sos}$ introduced by Lasserre and Parrilo and Sturmfels, which is computed using semidefinite programming, but a run time comparison shows that, in practice, the computation of $f_{gp}$ is much faster. The computation is simplest when the highest degree term of $f$ has the form $\\sum_{i=1}^n a_iX_i^{2d}$, $a_i>0$, $i=1,...,n$. The lower bounds for $f$ established in [6] are obtained by evaluating the objective function ...
A TRANSFORMATION PATH ALGORITHM FOR UNCONSTRAINED SIGNOMIAL GEOMETRIC PROGRAMMING
Institute of Scientific and Technical Information of China (English)
王燕军; 张可村
2004-01-01
In this paper we present a transformation path algorithm for Unconstrained Signomial Geometric Programming (USGP). The algorithm is proposed from a new point of view based on exploring the characteristics of USGP problem. Firstly by some stable transformations, a particular subproblem is derived which is very easy to solve.Secondly, a special path is formed conveniently. And then the step of the algorithm consists in finding a "good" point to the current iterate by choosing it along the special path and within a trust region. It is proved that the algorithm is globally convergent.
Geometric programming prediction of design trends for OMV protective structures
Mog, R. A.; Horn, J. R.
1990-01-01
The global optimization trends of protective honeycomb structural designs for spacecraft subject to hypervelocity meteroid and space debris are presented. This nonlinear problem is first formulated for weight minimization of the orbital maneuvering vehicle (OMV) using a generic monomial predictor. Five problem formulations are considered, each dependent on the selection of independent design variables. Each case is optimized by considering the dual geometric programming problem. The dual variables are solved for in terms of the generic estimated exponents of the monomial predictor. The primal variables are then solved for by conversion. Finally, parametric design trends are developed for ranges of the estimated regression parameters. Results specify nonmonotonic relationships for the optimal first and second sheet mass per unit areas in terms of the estimated exponents.
Geometric model of robotic arc welding for automatic programming
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Geometric information is important for automatic programming of arc welding robot. Complete geometric models of robotic arc welding are established in this paper. In the geometric model of weld seam, an equation with seam length as its parameter is introduced to represent any weld seam. The method to determine discrete programming points on a weld seam is presented. In the geometric model of weld workpiece, three class primitives and CSG tree are used to describe weld workpiece. Detailed data structure is presented. In pose transformation of torch, world frame, torch frame and active frame are defined, and transformation between frames is presented. Based on these geometric models, an automatic programming software package for robotic arc welding, RAWCAD, is developed. Experiments show that the geometric models are practical and reliable.
The Interaction Programming Problem
Institute of Scientific and Technical Information of China (English)
LI Rong-sheng; CHENG Ying
2001-01-01
Based upon the research to the economic equilibrium problems, we present a kind of new mathematical programming problem-interaction programming problem (abbreviated by IPP). The IPP is composed of two or multiple parametric programming problems which is interrelated with each other. The IPP reflects the equality and mutual benefit relationship between two (or among multiple) economic planners in an economic system. In essence, the IPP is similar to the generalized Nash equilibria (GNE) game which has been given several names in the literature: social equilibria games, pseudo-Nash equilibria games, and equilibrium programming problems. In this paper, we establish the mathematical model and some basic concepts to the IPP. We investigate the structure and the properties of the IPP. We also give a necessary and sufficient conditions for the existence of the equilibrium points to a kind of linear IPP.
Geometric MCMC for infinite-dimensional inverse problems
Beskos, Alexandros; Girolami, Mark; Lan, Shiwei; Farrell, Patrick E.; Stuart, Andrew M.
2017-04-01
Bayesian inverse problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms are characterized by deteriorating mixing times upon mesh-refinement, when the finite-dimensional approximations become more accurate. Such methods are typically forced to reduce step-sizes as the discretization gets finer, and thus are expensive as a function of dimension. Recently, a new class of MCMC methods with mesh-independent convergence times has emerged. However, few of them take into account the geometry of the posterior informed by the data. At the same time, recently developed geometric MCMC algorithms have been found to be powerful in exploring complicated distributions that deviate significantly from elliptic Gaussian laws, but are in general computationally intractable for models defined in infinite dimensions. In this work, we combine geometric methods on a finite-dimensional subspace with mesh-independent infinite-dimensional approaches. Our objective is to speed up MCMC mixing times, without significantly increasing the computational cost per step (for instance, in comparison with the vanilla preconditioned Crank-Nicolson (pCN) method). This is achieved by using ideas from geometric MCMC to probe the complex structure of an intrinsic finite-dimensional subspace where most data information concentrates, while retaining robust mixing times as the dimension grows by using pCN-like methods in the complementary subspace. The resulting algorithms are demonstrated in the context of three challenging inverse problems arising in subsurface flow, heat conduction and incompressible flow control. The algorithms exhibit up to two orders of magnitude improvement in sampling efficiency when compared with the pCN method.
Scale Problems in Geometric-Kinematic Modelling of Geological Objects
Siehl, Agemar; Thomsen, Andreas
To reveal, to render and to handle complex geological objects and their history of structural development, appropriate geometric models have to be designed. Geological maps, sections, sketches of strain and stress patterns are such well-known analogous two-dimensional models. Normally, the set of observations and measurements supporting them is small in relation to the complexity of the real objects they derive from. Therefore, modelling needs guidance by additional expert knowledge to bridge empty spaces which are not supported by data. Generating digital models of geological objects has some substantial advantages compared to conventional methods, especially if they are supported by an efficient database management system. Consistent 3D models of some complexity can be created, and experiments with time-dependent geological geometries may help to restore coherent sequences of paleogeological states. In order to cope with the problems arising from the combined usage of 3D-geometry models of different scale and resolution within an information system on subsurface geology, geometrical objects need to be annotated with information on the context, within which the geometry model has been established and within which it is valid, and methods supporting storage and retrieval as well as manipulation of geometry at different scales must also take into account and handle such context information to achieve meaningful results. An example is given of a detailed structural study of an open pit lignite mine in the Lower Rhine Basin.
Geometric Analysis of the Formation Problem for Autonomous Robots
Dorfler, Florian
2010-01-01
In the formation control problem for autonomous robots a distributed control law steers the robots to the desired target formation. A local stability result of the target formation can be derived by methods of linearization and center manifold theory or via a Lyapunov-based approach. It is well known that there are various other undesired invariant sets of the robots' closed-loop dynamics. This paper addresses a global stability analysis by a differential geometric approach considering invariant manifolds and their local stability properties. The theoretical results are then applied to the well-known example of a cyclic triangular formation and result in instability of all invariant sets other than the target formation.
Constant-work-space algorithms for geometric problems
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Tetsuo Asano
2011-07-01
Full Text Available Constant-work-space algorithms may use only constantly many cells of storage in addition to their input, which is provided as a read-only array. We show how to construct several geometric structures efficiently in the constant-work-space model. Traditional algorithms process the input into a suitable data structure (like a doubly-connected edge list that allows efficient traversal of the structure at hand. In the constant-work-space setting, however, we cannot afford to do this. Instead, we provide operations that compute the desired features on the fly by accessing the input with no extra space. The whole geometric structure can be obtained by using these operations to enumerate all the features. Of course, we must pay for the space savings by slower running times. While the standard data structure allows us to implement traversal operations in constant time, our schemes typically take linear time to read the input data in each step.We begin with two simple problems: triangulating a planar point set and finding the trapezoidal decomposition of a simple polygon. In both cases adjacent features can be enumerated in linear time per step, resulting in total quadratic running time to output the whole structure. Actually, we show that the former result carries over to the Delaunay triangulation, and hence the Voronoi diagram. This also means that we can compute the largest empty circle of a planar point set in quadratic time and constant work-space. As another application, we demonstrate how to enumerate the features of an Euclidean minimum spanning tree (EMST in quadratic time per step, so that the whole EMST can be found in cubic time using constant work-space.Finally, we describe how to compute a shortest geodesic path between two points in a simple polygon. Although the shortest path problem in general graphs is NL-complete (Jakoby and Tantau 2003, this constrained problem can be solved in quadratic time using only constant work-space.
Geometric Modeling Applications Interface Program (GMAP). Volume 1. Executive Overview
1989-09-01
Z . Code) 10. SOURCE OF FUNDING NOS. PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. NO. 11. TITLE (Include Security Classification) GEOMETRIC...342f CI FTR560240OOlU September 1989 SECTION 2 SCOPE OF GMAP GMAP focused on the generacion , control, and exchange of computer information to replace
Institute of Scientific and Technical Information of China (English)
顾利勤
2001-01-01
This paper discusses some properties of r-efficient solution and r-optimal solution for multiobjective programming problem.Some necessary and sufficient conditions as well as geometrical characters of these solutions are obtained.%讨论了多目标规划的r-有效解和r-最优解的某些性质，得到了几个充要条件和几何特性等结果.
Study on the Grey Polynomial Geometric Programming%灰色正项几何规划研究
Institute of Scientific and Technical Information of China (English)
罗党
2005-01-01
In the model of geometric programming, values of parameters cannot be gotten owing to data fluctuation and incompletion. But reasonable bounds of these parameters can be attained. This is to say, parameters of this model can be regarded as interval grey numbers. When the model contains grey numbers, it is hard for common programming method to solve them. By combining the common programming model with the grey system theory,and using some analysis strategies, a model of grey polynomial geometric programming, a model of θ positioned geometric programming and their quasi-optimum solution or optimum solution are put forward. At the same time, we also developed an algorithm for the problem.This approach brings a new way for the application research of geometric programming. An example at the end of this paper shows the rationality and feasibility of the algorithm.
Paas, Fred G.W.C.; van Merrienboer, Jeroen J.G.; van Merrienboer, J.J.G.
1994-01-01
Four computer-based training strategies for geometrical problem solving in the domain of computer numerically controlled machinery programming were studied with regard to their effects on training performance, transfer performance, and cognitive load. A low- and a high-variability conventional
Directory of Open Access Journals (Sweden)
D. L. Bricker
1997-01-01
Full Text Available The problem of assigning cell probabilities to maximize a multinomial likelihood with order restrictions on the probabilies and/or restrictions on the local odds ratios is modeled as a posynomial geometric program (GP, a class of nonlinear optimization problems with a well-developed duality theory and collection of algorithms. (Local odds ratios provide a measure of association between categorical random variables. A constrained multinomial MLE example from the literature is solved, and the quality of the solution is compared with that obtained by the iterative method of El Barmi and Dykstra, which is based upon Fenchel duality. Exploiting the proximity of the GP model of MLE problems to linear programming (LP problems, we also describe as an alternative, in the absence of special-purpose GP software, an easily implemented successive LP approximation method for solving this class of MLE problems using one of the readily available LP solvers.
A MESHLESS LOCAL PETROV-GALERKIN METHOD FOR GEOMETRICALLY NONLINEAR PROBLEMS
Institute of Scientific and Technical Information of China (English)
Xiong Yuanbo; Long Shuyao; Hu De'an; Li Guangyao
2005-01-01
Nonlinear formulations of the meshless local Petrov-Galerkin (MLPG) method are presented for geometrically nonlinear problems. The method requires no mesh in computation and therefore avoids mesh distortion difficulties in the large deformation analysis. The essential boundary conditions in the present formulation are imposed by a penalty method. An incremental and iterative solution procedure is used to solve geometrically nonlinear problems. Several examples are presented to demonstrate the effectiveness of the method in geometrically nonlinear problems analysis. Numerical results show that the MLPG method is an effective one and that the values of the unknown variable are quite accurate.
Developing shift problems to foster geometrical proof and understanding
Palha, S.; Dekker, R.; Gravemeijer, K.; van Hout-Wolters, B.
2013-01-01
Meaningful learning of formal mathematics in regular classrooms remains a problem in mathematics education. Research shows that instructional approaches in which students work collaboratively on tasks that are tailored to problem solving and reflection can improve students’ learning in experimental
Fuzzy Decision-Making Approach in Geometric Programming for a Single Item EOQ Model
Directory of Open Access Journals (Sweden)
Monalisha Pattnaik
2015-06-01
Full Text Available Background and methods: Fuzzy decision-making approach is allowed in geometric programming for a single item EOQ model with dynamic ordering cost and demand-dependent unit cost. The setup cost varies with the quantity produced/purchased and the modification of objective function with storage area in the presence of imprecisely estimated parameters are investigated. It incorporates all concepts of a fuzzy arithmetic approach, the quantity ordered, and demand per unit compares both fuzzy geometric programming technique and other models for linear membership functions. Results and conclusions: Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated through an example problem and the results discu ssed. Sensitivity analysis of the optimal solution is also studied with respect to changes in different parameter values.
Geometric Series: A New Solution to the Dog Problem
Dion, Peter; Ho, Anthony
2013-01-01
This article describes what is often referred to as the dog, beetle, mice, ant, or turtle problem. Solutions to this problem exist, some being variations of each other, which involve mathematics of a wide range of complexity. Herein, the authors describe the intuitive solution and the calculus solution and then offer a completely new solution…
Developing Shift Problems to Foster Geometrical Proof and Understanding
Palha, Sonia; Dekker, Rijkje; Gravemeijer, Koeno; van Hout-Wolters, Bernadette
2013-01-01
Meaningful learning of formal mathematics in regular classrooms remains a problem in mathematics education. Research shows that instructional approaches in which students work collaboratively on tasks that are tailored to problem solving and reflection can improve students' learning in experimental classrooms. However, these sequences involve…
Optimization of DC-DC Converters via Geometric Programming
Directory of Open Access Journals (Sweden)
U. Ribes-Mallada
2011-01-01
Full Text Available The paper presents a new methodology for optimizing the design of DC-DC converters. The magnitudes that we take into account are efficiency, ripples, bandwidth, and RHP zero placement. We apply a geometric programming approach, because the variables are positives and the constraints can be expressed in a posynomial form. This approach has all the advantages of convex optimization. We apply the proposed methodology to a boost converter. The paper also describes the optimum designs of a buck converter and a synchronous buck converter, and the method can be easily extended to other converters. The last example allows us to compare the efficiency and bandwidth between these optimal-designed topologies.
Geometric Generalisation of Surrogate Model-Based Optimisation to Combinatorial and Program Spaces
Directory of Open Access Journals (Sweden)
Yong-Hyuk Kim
2014-01-01
Full Text Available Surrogate models (SMs can profitably be employed, often in conjunction with evolutionary algorithms, in optimisation in which it is expensive to test candidate solutions. The spatial intuition behind SMs makes them naturally suited to continuous problems, and the only combinatorial problems that have been previously addressed are those with solutions that can be encoded as integer vectors. We show how radial basis functions can provide a generalised SM for combinatorial problems which have a geometric solution representation, through the conversion of that representation to a different metric space. This approach allows an SM to be cast in a natural way for the problem at hand, without ad hoc adaptation to a specific representation. We test this adaptation process on problems involving binary strings, permutations, and tree-based genetic programs.
Geometric properties of solutions to the total variation denoising problem
Chambolle, Antonin; Duval, Vincent; Peyré, Gabriel; Poon, Clarice
2017-01-01
This article studies the denoising performance of total variation (TV) image regularization. More precisely, we study geometrical properties of the solution to the so-called Rudin-Osher-Fatemi total variation denoising method. The first contribution of this paper is a precise mathematical definition of the ‘extended support’ (associated to the noise-free image) of TV denoising. It is intuitively the region which is unstable and will suffer from the staircasing effect. We highlight in several practical cases, such as the indicator of convex sets, that this region can be determined explicitly. Our second and main contribution is a proof that the TV denoising method indeed restores an image which is exactly constant outside a small tube surrounding the extended support. The radius of this tube shrinks toward zero as the noise level vanishes, and we are able to determine, in some cases, an upper bound on the convergence rate. For indicators of so-called ‘calibrable’ sets (such as disks or properly eroded squares), this extended support matches the edges, so that discontinuities produced by TV denoising cluster tightly around the edges. In contrast, for indicators of more general shapes or for complicated images, this extended support can be larger. Beside these main results, our paper also proves several intermediate results about fine properties of TV regularization, in particular for indicators of calibrable and convex sets, which are of independent interest.
The Parabolas of Artzt in the Solution of a Geometric Problem of Minimum Length
Klaoudatos, Nikos
2011-01-01
The article describes the solution of a geometric problem and how this problem was formed. During the investigation process, I discovered that the inscribed parabola in a triangle, known as the parabola of Artzt, a mathematical subject developed almost 120 years ago, was the decisive idea which directed me towards the solution. Moreover, in the…
Directory of Open Access Journals (Sweden)
Yogeesha C.B
2014-09-01
Full Text Available The classical methods have limited scope in practical applications as some of them involve objective functions which are not continuous and/or differentiable. Evolutionary Computation is a subfield of artificial intelligence that involves combinatorial optimization problems. Travelling Salesperson Problem (TSP, which considered being a classic example for Combinatorial Optimization problem. It is said to be NP-Complete problem that cannot be solved conventionally particularly when number of cities increase. So Evolutionary techniques is the feasible solution to such problem. This paper explores an evolutionary technique: Geometric Hopfield Neural Network model to solve Travelling Salesperson Problem. Paper also achieves the results of Geometric TSP and compares the result with one of the existing widely used nature inspired heuristic approach Ant Colony Optimization Algorithms (ACA/ACO to solve Travelling Salesperson Problem.
Yildiz, Avni
2016-01-01
Geometric constructions have already been of interest to mathematicians. However, studies on geometric construction are not adequate in the relevant literature. Moreover, these studies generally focus on how secondary school gifted students solve non-routine mathematical problems. The present study aims to examine the geometric construction…
Santoprete, Manuele
2002-01-01
Resorting to classical techniques of Riemannian geometry we develop a geometrical method suitable to investigate the nonintegrability of geodesic flows and of natural Hamiltonian systems. Then we apply such method to the Anisotropic Kepler Problem (AKP) and we prove that it is not analytically integrable.
A restricted Steiner tree problem is solved by Geometric Method II
Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu
2013-03-01
The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.
A Geometric Approach to the Kronecker Problem I: The Two Row Case
Indian Academy of Sciences (India)
Bharat Adsul; K V Subrahmanyam
2008-05-01
Given two irreducible representations , of the symmetric group $S_d$, the Kronecker problem is to find an explicit rule, giving the multiplicity of an irreducible representation, , of $S_d$, in the tensor product of and . We propose a geometric approach to investigate this problem. We demonstrate its effectiveness by obtaining explicit formulas for the tensor product multiplicities, when the irreducible representations are parameterized by partitions with at most two rows.
Geometric tools for solving the FDI problem for linear periodic discrete-time systems
Longhi, Sauro; Monteriù, Andrea
2013-07-01
This paper studies the problem of detecting and isolating faults in linear periodic discrete-time systems. The aim is to design an observer-based residual generator where each residual is sensitive to one fault, whilst remaining insensitive to the other faults that can affect the system. Making use of the geometric tools, and in particular of the outer observable subspace notion, the Fault Detection and Isolation (FDI) problem is formulated and necessary and solvability conditions are given. An algorithmic procedure is described to determine the solution of the FDI problem.
A Greedy Algorithm for a Special Class of Geometric Set Covering Problems
DEFF Research Database (Denmark)
Stolpe, Mathias; Bechmann, Andreas
of a geometric set covering problem we propose a greedy type algorithm. We also propose a linear mixed 0 – 1 formulation of the problem. For each problem instance this formulation is solved by a commercial branch-andcut solver and the results are used to validate the quality of the solution from the greedy...... algorithm. The greedy algorithm finds the minimum number of squares for all but one problem instances from a set of 26 representative real-world examples.......We consider the problem of covering a set of given points in the plane by the smallest number of axis aligned squares of a given fixed size. This problem is of importance for computational fluid dynamics simulations of both onshore and offshore wind turbine parks. For this special case...
The group theory for solving electromagnetic scattering problems with geometric symmetric structure
Institute of Scientific and Technical Information of China (English)
朱峰; 杨海川; 任朗
1997-01-01
It is a very important issue to reduce computer storage and calculation time for matrix in solving scattering field by making use of geometric and physical symmetric features of a scattering body. A general definition for the symmetric and anti-symmetric structure is given by applying the group theory in mathematics and a general method for treating the electromagnetic scattering problems with symmetry is proposed. An example for applying the theory mentioned above is also given.
The geometric Cauchy problem for surfaces with Lorentzian harmonic Gauss maps
DEFF Research Database (Denmark)
Brander, David; Svensson, Martin
2013-01-01
The geometric Cauchy problem for a class of surfaces in a pseudo-Riemannian manifold of dimension 3 is to find the surface which contains a given curve with a prescribed tangent bundle along the curve. We consider this problem for constant negative Gauss curvature surfaces (pseudospherical surfaces...... representation for surfaces associated with Lorentzian harmonic maps (1-1 wave maps) into symmetric spaces, developed since the 1990's. Explicit formulae for the potentials in terms of the prescribed data are given, and some applications are considered....
Directory of Open Access Journals (Sweden)
Deniz Özen
2013-03-01
Full Text Available The aim of this study is to investigate pre-service elementary mathematics teachers’ open geometric problem solving process in a Dynamic Geometry Environment. With its qualitative inquiry based research design employed, the participants of the study are three pre-service teachers from 4th graders of the Department of Elementary Mathematics Teaching. In this study, clinical interviews, screencaptures of the problem solving process in the Cabri Geomery Environment, and worksheets included 2 open geometry problems have been used to collect the data. It has been investigated that all the participants passed through similar recursive phases as construction, exploration, conjecture, validate, and justification in the problem solving process. It has been thought that this study provide a new point of view to curriculum developers, teachers and researchers
Optimal Resource Allocation for Network Protection: A Geometric Programming Approach
Preciado, Victor M; Enyioha, Chinwendu; Jadbabaie, Ali; Pappas, George
2013-01-01
We study the problem of containing spreading processes in arbitrary directed networks by distributing protection resources throughout the nodes of the network. We consider two types of protection resources are available: (i) Preventive resources able to defend nodes against the spreading (such as vaccines in a viral infection process), and (ii) corrective resources able to neutralize the spreading after it has reached a node (such as antidotes). We assume that both preventive and corrective resources have an associated cost and study the problem of finding the cost-optimal distribution of resources throughout the nodes of the network. We analyze these questions in the context of viral spreading processes in directed networks. We study the following two problems: (i) Given a fixed budget, find the optimal allocation of preventive and corrective resources in the network to achieve the highest level of containment, and (ii) when a budget is not specified, find the minimum budget required to control the spreading...
Effects of geometric head model perturbations on the EEG forward and inverse problems.
von Ellenrieder, Nicolás; Muravchik, Carlos H; Nehorai, Arye
2006-03-01
We study the effect of geometric head model perturbations on the electroencephalography (EEG) forward and inverse problems. Small magnitude perturbations of the shape of the head could represent uncertainties in the head model due to errors on images or techniques used to construct the model. They could also represent small scale details of the shape of the surfaces not described in a deterministic model, such as the sulci and fissures of the cortical layer. We perform a first-order perturbation analysis, using a meshless method for computing the sensitivity of the solution of the forward problem to the geometry of the head model. The effect on the forward problem solution is treated as noise in the EEG measurements and the Cramér-Rao bound is computed to quantify the effect on the inverse problem performance. Our results show that, for a dipolar source, the effect of the perturbations on the inverse problem performance is under the level of the uncertainties due to the spontaneous brain activity. Thus, the results suggest that an extremely detailed model of the head may be unnecessary when solving the EEG inverse problem.
Extensions to the Multilevel Programming Problem
1988-05-01
READS IN A 0-1 BILEVEL PROGRAMMING C PROBLEM (BLPP) AND CREATES THE MATHEMATICAL C PROGRAMMING PROBLEM WHICH CAN BE SOLVED TO FIND C THE SOLUTION OF THE...CODES DEVELOPED BY DR. PAUL A. JENSEN. C IT IS USED TO SOLVE THE 0-1 INTEGER PROGRAMMING C PROBLEM DERIVED FROM THE 0-1 BLPP. C IMPLICIT INTEGER (A-Z...233 PROGRAM BLPPRD C C *****PURPOSE C THIS PROGRAM READS IN A BILEVEL PROGRAMMING C PROBLEM (BLPP) OR A MIXED INTEGER BLPP AND CREATES C THE
The spectrum of the torus profile to a geometric variational problem with long range interaction
Ren, Xiaofeng; Wei, Juncheng
2017-08-01
The profile problem for the Ohta-Kawasaki diblock copolymer theory is a geometric variational problem. The energy functional is defined on sets in R3 of prescribed volume and the energy of an admissible set is its perimeter plus a long range interaction term related to the Newtonian potential of the set. This problem admits a solution, called a torus profile, that is a set enclosed by an approximate torus of the major radius 1 and the minor radius q. The torus profile is both axially symmetric about the z axis and reflexively symmetric about the xy-plane. There is a way to set up the profile problem in a function space as a partial differential-integro equation. The linearized operator L of the problem at the torus profile is decomposed into a family of linear ordinary differential-integro operators Lm where the index m = 0 , 1 , 2 , … is called a mode. The spectrum of L is the union of the spectra of the Lm's. It is proved that for each m, when q is sufficiently small, Lm is positive definite. (0 is an eigenvalue for both L0 and L1, due to the translation and rotation invariance.) As q tends to 0, more and more Lm's become positive definite. However no matter how small q is, there is always a mode m of which Lm has a negative eigenvalue. This mode grows to infinity like q - 3 / 4 as q → 0.
Kynigos, Chronis
1993-01-01
Used 2 12-year-old children to investigate deductive and inductive reasoning in plane geometry. A LOGO microworld was programmed to measure distances and turns relative to points on the plane. Learning environments like this may enhance formation of inductive geometrical understandings. (Contains 44 references.) (LDR)
Measurement problem in PROGRAM UNIVERSE
Energy Technology Data Exchange (ETDEWEB)
Noyes, H.P.; Gefwert, C.
1984-12-01
We present a discrete theory that meets the measurement problem in a new way. We generate a growing universe of bit strings, labeled by 2/sup 127/ + 136 strings organized by some representation of the closed, four level, combinatorial hierarchy, of bit-length N/sub 139/ greater than or equal to 139. The rest of the strings for each label, which grow in both length and number, are called addresses. The generating algorithm, called PROGRAM UNIVERSE, starts from a random choice between the two symbols ''0'' and ''1'' and grows (a) by discriminating between two randomly chosen strings and adjoining a novel result to the universe, or when the string so generated is not novel, by (b) adjoining a randomly chosen bit at the growing end of each string. We obtain, by appropriate definitions and interpretations, stable ''particles'' which satisfy the usual relativistic kinematics and quantized angular momentum without being localizable in a continuum space-time. The labeling scheme is congruent with the ''standard model'' of quarks and leptons with three generations, but for the problem at hand, the implementation of this aspect of the theory is unimportant. What matters most is that (a) these complicated ''particles'' have the periodicities familiar from relativistic ''deBroglie waves'' and resolve in a discrete way the ''wave-particle dualism'' and (b) can be ''touched'' by our discrete equivalent of ''soft photons'' in such a way as to follow, macroscopically, the usual Rutherford scattering trajectories with the associated bound states. Thus our theory could provide a discrete description of ''measurement'' in a way that allows no conceptual barrier between the ''micro'' and the ''macro'' worlds, if we are willing to base our physics on
Iterative Solutions to the Inverse Geometric Problem for Manipulators with no Closed Form Solution
Directory of Open Access Journals (Sweden)
Pål Johan From
2008-07-01
Full Text Available A set of new iterative solutions to the inverse geometric problem is presented. The approach is general and does not depend on intersecting axes or calculation of the Jacobian. The solution can be applied to any manipulator and is well suited for manipulators for which convergence is poor for conventional Jacobian-based iterative algorithms. For kinematically redundant manipulators, weights can be applied to each joint to introduce stiffness and for collision avoidance. The algorithm uses the unit quaternion to represent the position of each joint and calculates analytically the optimal position of the joint when only the respective joint is considered. This sub-problem is computationally very efficient due to the analytical solution. Several algorithms based on the solution of this sub-problem are presented. For difficult problems, for which the initial condition is far from a solution or the geometry of the manipulator makes the solution hard to reach, it is shown that the algorithm finds a solution fairly close to the solution in only a few iterations.
To the problem 6 of emplacement of triangular geometric net on the sphere
Directory of Open Access Journals (Sweden)
Travush Vladimir
2017-01-01
Full Text Available Thesphere creates the minimal surface of enclosing structures and has unique resource saving qualities which makes it indispensable in the construction of “smart buildings». One of the methods of formation of triangular networks in the sphere was investigated. Conditions of the problem of locating a triangular network in the area were established. The evaluation criterion of solution effectiveness of the problem is the minimum number of type-sizes of dome panels, the possibility of pre-assembly and pre-stressing. The solution of the problem of the triangular network emplacement in a compatible spherical triangle on the sphere variant was provided. The problem of the emplacement of regular and irregular hexagons on the sphere, inscribed in a circles, i.e., flat figures or composed ones of spherical triangles with minimum dimensions of the ribs, has an effective solution in the form of a network, formed on the basis of minimum radii circles, i.e., circles on a sphere obtained by the touch of three adjacent circles whose centers are at the shortest distance from each other. The optimization of triangular geometric network on a sphere on the criterion of minimum sizes of elements can be solved by emplacementin the system the irregular hexagons inscribed in circles of minimal sizes, the maximum of regular hexagons.
Application of PID controller to 2D differential geometric guidance problem
Institute of Scientific and Technical Information of China (English)
Chaoyong LI; Wuxing JING
2007-01-01
This paper presents the application of the proportional-integral-derivative (PID) controller to the flight control system (FCS) for two-dimensional (2D) differential geometric (DG) guidance and control problem. In particular,the performance of the designed FCS is investigated. To this end, the commanded angle-of-attack is firstly developed in the time domain using the classical DG formulations. Then, the classical PID controller is introduced to develop a FCS so as to form the 2D DG guidance and control system, and the PID controller parameters are determined by the Ziegler-Nichols method as well as the Routh-Hurwitz stability algorithm to guarantee the convergence of the system error. The results demonstrate that the designed controller yields a fast responding system, and the resulting DG guidance and control system is viable and effective in a realistic missile defense engagement.
Geometrical Modification of Learning Vector Quantization Method for Solving Classification Problems
Directory of Open Access Journals (Sweden)
Korhan GÜNEL
2016-09-01
Full Text Available In this paper, a geometrical scheme is presented to show how to overcome an encountered problem arising from the use of generalized delta learning rule within competitive learning model. It is introduced a theoretical methodology for describing the quantization of data via rotating prototype vectors on hyper-spheres.The proposed learning algorithm is tested and verified on different multidimensional datasets including a binary class dataset and two multiclass datasets from the UCI repository, and a multiclass dataset constructed by us. The proposed method is compared with some baseline learning vector quantization variants in literature for all domains. Large number of experiments verify the performance of our proposed algorithm with acceptable accuracy and macro f1 scores.
Geometric characterization for the least Lagrangian action of n-body problems
Institute of Scientific and Technical Information of China (English)
ZHANG; Shiqing
2001-01-01
［1］Manev, G., La gravitation et l'énergie au zéro, Comptes Rendus, 924, 78: 259.［2］Diacu, F. N., Near-collision dynamics for particle systems with quasihomogeneous potentials, J. of Diff. Equ., 996, 28: 58.［3］Ambrosetti, A., Coti Zelati, V., Periodic Solutions of Singular Lagrangian Systems, Basel: Birkhuser, 993.［4］Arnold, V., Kozlov, V., Neishtadt, A., Dynamical Systems (iii): Mathematical Aspects of Classical and Celestial Mechanics, Berlin: Springer-Verlag, 988.［5］Chenciner, A., Desolneux, N., Minima de l'intégrale d'action et équilibres relatifs de n corps, C R Acad. Sci. Paris, serie I, 998, 326: 209.［6］Coti Zelati, V., The periodic solutions of n-body type problems, Ann IHP Anal nonlinéaire, 990, 7: 477.［7］Euler, L., De motu rectilineo trium corprum se mutuo attrahentium, Novi. Comm. Acad. Sci. Imp. Petropll, 767: 45.［8］Gordon, W., A minimizing property of Keplerian orbits, Amer. J. Math., 977, 99: 96.［9］Lagrange, J., Essai sur le problé me des trois corps, 772, Ouvres, 783, 3: 229.［10］Long, Y., Zhang, S. Q., Geometric characterization for variational minimization solutions of the 3-body problem, Chinese Science Bulletin, 999, 44(8): 653.［11］Long, Y., Zhang, S. Q., Geometric characterization for variational minimization solutions of the 3-body problem with fixed energy, J. of Diff. Equ., 2000, 60: 422.［12］Meyer, K., Hall, G., Introduction to Hamiltonian systems and the n-body problems, Berlin: Springer-Verlag,992.［13］Serra, E., Terracini, S., Collisionless periodic solutions to some three-body problems, Arch. Rational Mech. Anal., 992, 20: 305.［14］Siegle, C., Moser, J., Lectures on Celestial Mechanics, Berlin: Springer-Verlag, 97.［15］Wintner, A., Analytical Foundations of Celestial Mechanics, Princeton: Princeton University Press, 94.［16］Hardy, G., Littlewood, J., Pólya, G., Inequalities, 2nd ed., Cambridge: Combridge University Press, 952.
S-duality of boundary conditions and the Geometric Langlands program
Gaiotto, Davide
2016-01-01
Maximally supersymmetric gauge theory in four dimensions admits local boundary conditions which preserve half of the bulk supersymmetries. The S-duality of the bulk gauge theory can be extended in a natural fashion to act on such half-BPS boundary conditions. The purpose of this note is to explain the role these boundary conditions can play in the Geometric Langlands program. In particular, we describe how to obtain pairs of Geometric Langland dual objects from S-dual pairs of half-BPS boundary conditions.
A discrete geometric formulation for eddy-current problems in fusion devices
Bettini, Paolo; Furno Palumbo, Maurizio; Specogna, Ruben
2014-03-01
All thermonuclear controlled fusion devices under construction or design have such high performances to require a special care in the dimensioning of various components, specifically from the electromagnetic point of view. To this purpose, it is fundamental to develop models which are both accurate (i.e. able to describe the physical phenomena) and predictive (i.e. useful not only to explain what happens in running experiments, but also to reliably extrapolate to other range of parameters). The dynamics of fusion plasmas is often conveniently described by Magneto-Hydro-Dynamics (MHD) equations, which predict that some unstable evolution modes may exist. On the other hand, the complexity of the intrinsically 3D model of the interactions between a realistic unstable plasma, the surrounding passive structures (important to guarantee a good MHD stability) and the active conductors (coils) require the numerical solution of challenging electromagnetic problems. In this work a discrete geometric formulation for eddy-current problems in the frequency domain is developed; the magnetic fields produced by a typical active coil system is calculated in the presence of 3D conductive structures.
Badriev, I. B.; Banderov, V. V.; Makarov, M. V.
2017-06-01
In this paper we consider the geometrically nonlinear problem of determining the equilibrium position of a sandwich plate consisting of two external carrier layers and located between transversely soft core, connected with carrier layer by means of adhesive joint. We investigate the generalized statement of the problem. For its numerical implementation we offer a two-layer iterative process and investigate the convergence of the method. Numerical experiments are carried out for the model problem.
Semantic Solutions to Program Analysis Problems
Tobin-Hochstadt, Sam
2011-01-01
Problems in program analysis can be solved by developing novel program semantics and deriving abstractions conventionally. For over thirty years, higher-order program analysis has been sold as a hard problem. Its solutions have required ingenuity and complex models of approximation. We claim that this difficulty is due to premature focus on abstraction and propose a new approach that emphasizes semantics. Its simplicity enables new analyses that are beyond the current state of the art.
An Algorithm for Solving Quadratic Programming Problems
Directory of Open Access Journals (Sweden)
V. Moraru
1997-08-01
Full Text Available Herein is investigated the method of solution of quadratic programming problems. The algorithm is based on the effective selection of constraints. Quadratic programming with constraints-equalities are solved with the help of an algorithm, so that matrix inversion is avoided, because of the more convenient organization of the Calculus. Optimal solution is determined in a finite number of iterations. It is discussed the extension of the algorithm over solving quadratic non-convex programming problems.
Mitchell, Lawrence; Müller, Eike Hermann
2016-12-01
The implementation of efficient multigrid preconditioners for elliptic partial differential equations (PDEs) is a challenge due to the complexity of the resulting algorithms and corresponding computer code. For sophisticated (mixed) finite element discretisations on unstructured grids an efficient implementation can be very time consuming and requires the programmer to have in-depth knowledge of the mathematical theory, parallel computing and optimisation techniques on manycore CPUs. In this paper we show how the development of bespoke multigrid preconditioners can be simplified significantly by using a framework which allows the expression of the each component of the algorithm at the correct abstraction level. Our approach (1) allows the expression of the finite element problem in a language which is close to the mathematical formulation of the problem, (2) guarantees the automatic generation and efficient execution of parallel optimised low-level computer code and (3) is flexible enough to support different abstraction levels and give the programmer control over details of the preconditioner. We use the composable abstractions of the Firedrake/PyOP2 package to demonstrate the efficiency of this approach for the solution of strongly anisotropic PDEs in atmospheric modelling. The weak formulation of the PDE is expressed in Unified Form Language (UFL) and the lower PyOP2 abstraction layer allows the manual design of computational kernels for a bespoke geometric multigrid preconditioner. We compare the performance of this preconditioner to a single-level method and hypre's BoomerAMG algorithm. The Firedrake/PyOP2 code is inherently parallel and we present a detailed performance analysis for a single node (24 cores) on the ARCHER supercomputer. Our implementation utilises a significant fraction of the available memory bandwidth and shows very good weak scaling on up to 6,144 compute cores.
Integer Programming Models for Computational Biology Problems
Institute of Scientific and Technical Information of China (English)
Giuseppe Lancia
2004-01-01
The recent years have seen an impressive increase in the use of Integer Programming models for the solution of optimization problems originating in Molecular Biology. In this survey, some of the most successful Integer Programming approaches are described, while a broad overview of application areas being is given in modern Computational Molecular Biology.
Enhancing creative problem solving in an integrated visual art and geometry program: A pilot study
Schoevers, E.M.; Kroesbergen, E.H.
2017-01-01
This article describes a new pedagogical method, an integrated visual art and geometry program, which has the aim to increase primary school students' creative problem solving and geometrical ability. This paper presents the rationale for integrating visual art and geometry education. Furthermore
Sadjadi, Seyed Jafar; Hamidi Hesarsorkh, Aghil; Mohammadi, Mehdi; Bonyadi Naeini, Ali
2014-08-01
Coordination and harmony between different departments of a company can be an important factor in achieving competitive advantage if the company corrects alignment between strategies of different departments. This paper presents an integrated decision model based on recent advances of geometric programming technique. The demand of a product considers as a power function of factors such as product's price, marketing expenditures, and consumer service expenditures. Furthermore, production cost considers as a cubic power function of outputs. The model will be solved by recent advances in convex optimization tools. Finally, the solution procedure is illustrated by numerical example.
Solving a Fully Fuzzy Linear Programming Problem through Compromise Programming
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
In the current literatures, there are several models of fully fuzzy linear programming (FFLP) problems where all the parameters and variables were fuzzy numbers but the constraints were crisp equality or inequality. In this paper, an FFLP problem with fuzzy equality constraints is discussed, and a method for solving this FFLP problem is also proposed. We first transform the fuzzy equality constraints into the crisp inequality ones using the measure of the similarity, which is interpreted as t...
Energy Technology Data Exchange (ETDEWEB)
Mitchell, J.S.B. [State Univ. of New York, Stony Brook, NY (United States)
1996-12-31
We show that any rectilinear polygonal subdivision in the plane can be converted into a {open_quotes}guillotine{close_quote} subdivision whose length is at most twice that of the original subdivision. {open_quote}Guillotine{close_quotes} subdivisions have a simple recursive structure that allows one to search for {open_quotes}optimal{close_quotes} such subdivisions in polynomial time, using dynamic programming. In particular, a consequence of our main theorem is a very simple proof that the k-MST problem in the plane has a constant factor polynomial-time approximation algorithm, and the constant factor that we obtain is a substantial improvement over all previous bounds: We obtain a factor of 2 for the L{sub 1} metric, and a factor of 2{radical}2 for the L{sub 2} (Euclidean) metric.
Design Optimization with Geometric Programming for Core Type Large Power Transformers
Directory of Open Access Journals (Sweden)
Orosz Tamás
2014-10-01
Full Text Available A good transformer design satisfies certain functions and requirements. We can satisfy these requirements by various designs. The aim of the manufacturers is to find the most economic choice within the limitations imposed by the constraint functions, which are the combination of the design parameters resulting in the lowest cost unit. One of the earliest application of the Geometric Programming [GP] is the optimization of power transformers. The GP formalism has two main advantages. First the formalism guarantees that the obtained solution is the global minimum. Second the new solution methods can solve even large-scale GPs extremely efficiently and reliably. The design optimization program seeks a minimum capitalized cost solution by optimally setting the transformer's geometrical and electrical parameters. The transformer's capitalized cost chosen for object function, because it takes into consideration the manufacturing and the operational costs. This paper considers the optimization for three winding, three phase, core-form power transformers. This paper presents the implemented transformer cost optimization model and the optimization results.
Numerical nonlinear complex geometrical optics algorithm for the 3D Calderón problem
DEFF Research Database (Denmark)
Delbary, Fabrice; Knudsen, Kim
2014-01-01
computer implementation of the full nonlinear algorithm is given. First a boundary integral equation is solved by a Nystrom method for the traces of the complex geometrical optics solutions, second the scattering transform is computed and inverted using fast Fourier transform, and finally a boundary value...
Lyapunov vs. geometrical stability analysis of the Kepler and the restricted three body problems
DEFF Research Database (Denmark)
Yahalom, A.; Levitan, J.; Lewkowicz, M.
2011-01-01
to move in a very interesting and intricate but periodic trajectory; however, the standard Lyapunov analysis, as well as methods based on the parametric variation of curvature associated with the Jacobi metric, incorrectly predict chaotic behavior. The geometric approach predicts the correct stable motion...
A Geometric Approach to Diagnosis Applied to A Ship Propulsion Problem
DEFF Research Database (Denmark)
Lootsma, T.F.; Izadi-Zamanabadi, Roozbeh; Nijmeijer, H.
A geometric approach to FDI diagnosis for input-affine nonlinear systems is briefly described and applied to a ship propulsion benchmark. The analysis method is used to examine the possibility of detecting and isolating predefined faults in the system. The considered faults cover sensor, actuator...
Employee assistance program treats personal problems.
Bednarek, R J; Featherston, H J
1984-03-01
Though the concept of employee assistance programs (EAPs) is widely accepted throughout business and industry, few hospitals have established similar channels for dealing with workers whose personal problems cause work-related problems. Among the reasons for the health care profession's lack of involvement in this area are: lack of information about costs and benefits of EAPs; the hospital's multidisciplinary environment in which standards of employee competence and behavior are set by persons from many disciplines; hospital working hours; and health care workers' attitudes about their vulnerability to illness. St. Benedict's Hospital, Ogden, UT, however, has confronted the question of how to demonstrate Christian concern for its employees. St. Benedict's EAP, the Helping Hand, which was created in 1979, combines progressive disciplinary action with the opportunity for early intervention in and treatment of employees' personal problems. When a worker with personal problems is referred to the EAP coordinator, he or she is matched with the appropriate community or hospital resource for treatment. Supervisors are trained to identify employee problems and to focus on employee job performance rather than on attempting to diagnose the problem. St. Benedict's records during the program's first three years illustrate the human benefits as well as the cost savings of an EAP. Of 92 hospital employees who took part in the EAP, 72 improved their situations or resolved their problems. The hospital's turnover rates declined from 36 percent to 20 percent, and approximately $40,800 in turnover and replacement costs were saved.
Bivium as a Mixed Integer Programming Problem
DEFF Research Database (Denmark)
Borghoff, Julia; Knudsen, Lars Ramkilde; Stolpe, Mathias
2009-01-01
Trivium is a stream cipher proposed for the eSTREAM project. Raddum introduced some reduced versions of Trivium, named Bivium A and Bivium B. In this article we present a numerical attack on the Biviums. The main idea is to transform the problem of solving a sparse system of quadratic equations...... over $GF(2)$ into a combinatorial optimization problem. We convert the Boolean equation system into an equation system over $\\mathbb{R}$ and formulate the problem of finding a $0$-$1$-valued solution for the system as a mixed-integer programming problem. This enables us to make use of several...... algorithms in the field of combinatorial optimization in order to find a solution for the problem and recover the initial state of Bivium. In particular this gives us an attack on Bivium B in estimated time complexity of $2^{63.7}$ seconds. But this kind of attack is also applicable to other cryptographic...
A SPLITTING METHOD FOR QUADRATIC PROGRAMMING PROBLEM
Institute of Scientific and Technical Information of China (English)
魏紫銮
2001-01-01
A matrix splitting method is presented for minimizing a quadratic programming (QP)problem, and a general algorithm is designed to solve the QP problem and generates a sequence of iterative points. We prove that the sequence generated by the algorithm converges to the optimal solution and has an R-linear rate of convergence if the QP problem is strictly convex and nondegenerate, and that every accumulation point of the sequence generated by the general algorithm is a KKT point of the original problem under the hypothesis that the value of the objective function is bounded below on the constrained region, and that the sequence converges to a KKT point if the problem is nondegenerate and the constrained region is bounded.
Timergaliev, S. N.
2009-06-01
This paper deals with the proof of the existence of solutions of a geometrically and physically nonlinear boundary value problem for shallow Timoshenko shells with the transverse shear strains taken into account. The shell edge is assumed to be partly fixed. It is proposed to study the problem by a variational method based on searching the points of minimum of the total energy functional for the shell-load system in the space of generalized displacements. We show that there exists a generalized solution of the problemon which the total energy functional attains its minimum on a weakly closed subset of the space of generalized displacements.
Women in Jail: Problems, Programs and Resources.
Roy, Marjorie Brown
This manual is designed to assist those individuals or groups responsible for developing educational and vocational programs for women in jail. The first section identifies the needs and problems of women in jail, focussing on discrimination against poor women unable to afford bail, the nonviolent nature of women's crimes, and the inequity of jail…
Ozkan, Aysegul; Sitharam, Meera; Kurnikova, Maria
2014-01-01
EASAL (efficient atlasing and sampling of assembly landscapes) is a recently reported geometric method for representing, visualizing, sampling and computing integrals over the potential energy landscape tailored for small molecular assemblies. EASAL's efficiency arises from the fact that small assembly landscapes permit the use of so-called Cayley parameters (inter-atomic distances) for geometric representation and sampling of the assembly configuration space regions; this results in their isolation, convexification, customized sampling and systematic traversal using a comprehensive topological roadmap. By sampling the assembly landscape of 2 TransMembrane Helices, with short-range pair-potentials, this paper demonstrates that EASAL provides reasonable coverage of crucial but narrow regions of low effective dimension with much fewer samples and computational resources than traditional MonteCarlo or Molecular Dynamics based sampling. Promising avenues are discussed, for combining the complementary advantages o...
Programming languages for business problem solving
Wang, Shouhong
2007-01-01
It has become crucial for managers to be computer literate in today's business environment. It is also important that those entering the field acquire the fundamental theories of information systems, the essential practical skills in computer applications, and the desire for life-long learning in information technology. Programming Languages for Business Problem Solving presents a working knowledge of the major programming languages, including COBOL, C++, Java, HTML, JavaScript, VB.NET, VBA, ASP.NET, Perl, PHP, XML, and SQL, used in the current business computing environment. The book examin
Stalactite Growth as a Free-Boundary Problem: A Geometric Law and Its Platonic Ideal
Short, Martin B.; Baygents, James C.; Beck, J. Warren; Stone, David A.; Toomey, Rickard S.; Goldstein, Raymond E.
2005-01-01
The chemical mechanisms underlying the growth of cave formations such as stalactites are well known, yet no theory has yet been proposed which successfully accounts for the dynamic evolution of their shapes. Here we consider the interplay of thin-film fluid dynamics, calcium carbonate chemistry, and CO2 transport in the cave to show that stalactites evolve according to a novel local geometric growth law which exhibits extreme amplification at the tip as a consequence of the locally-varying fluid layer thickness. Studies of this model show that a broad class of initial conditions is attracted to an ideal shape which is strikingly close to a statistical average of natural stalactites.
Pawlak, Tomasz P; Krawiec, Krzysztof
2017-02-16
Program semantics is a promising recent research thread in Genetic Programming (GP). Over a dozen of semantic-aware search, selection, and initialization operators for GP have been proposed to date. Some of those operators are designed to exploit the geometric properties of semantic space, while some others focus on making offspring effective, i.e., semantically different from their parents. Only a small fraction of previous works aimed at addressing both these features simultaneously. In this paper, we propose a suite of competent operators that combine effectiveness with geometry for population initialization, mate selection, mutation and crossover. We present a theoretical rationale behind these operators and compare them experimentally to operators known from literature on symbolic regression and Boolean function synthesis benchmarks. We analyze each operator in isolation as well as verify how they fare together in an evolutionary run, concluding that the competent operators are superior on a wide range of performance indicators, including best-of-run fitness, test-set fitness, and program size.
A prefiltered cuckoo search algorithm with geometric operators for solving Sudoku problems.
Soto, Ricardo; Crawford, Broderick; Galleguillos, Cristian; Monfroy, Eric; Paredes, Fernando
2014-01-01
The Sudoku is a famous logic-placement game, originally popularized in Japan and today widely employed as pastime and as testbed for search algorithms. The classic Sudoku consists in filling a 9 × 9 grid, divided into nine 3 × 3 regions, so that each column, row, and region contains different digits from 1 to 9. This game is known to be NP-complete, with existing various complete and incomplete search algorithms able to solve different instances of it. In this paper, we present a new cuckoo search algorithm for solving Sudoku puzzles combining prefiltering phases and geometric operations. The geometric operators allow one to correctly move toward promising regions of the combinatorial space, while the prefiltering phases are able to previously delete from domains the values that do not conduct to any feasible solution. This integration leads to a more efficient domain filtering and as a consequence to a faster solving process. We illustrate encouraging experimental results where our approach noticeably competes with the best approximate methods reported in the literature.
Directory of Open Access Journals (Sweden)
Kotb A.E.H.M. Kotb
2011-01-01
Full Text Available Problem statement: In this study, we provide a simple method to determine the inventory policy of probabilistic single-item Economic Order Quantity (EOQ model, that has varying order cost and zero lead time. The model is restricted to the expected holding cost and the expected available limited storage space. Approach: The annual expected total cost is composed of three components (expected purchase cost, expected ordering cost and expected holding cost. The problem is then solved using a modified Geometric Programming method (GP. Results: Using the annual expected total cost to determine the optimal solutions, number of periods, maximum inventory level and minimum expected total cost per period. A classical model is derived and numerical example is solved to confirm the model. Conclusion/Recommendations: The results indicated the total cost decreased with changes in optimal solutions. Possible future extension of this model was include continuous decreasing ordering function of the number of periods and introducing expected annual demand rate as a decision variable.
A Trust Region Algorithm for Solving Bilevel Programming Problems
Institute of Scientific and Technical Information of China (English)
Guo-shan LIU; Shi-qin XU; Ji-ye HAN
2013-01-01
In this paper,we present a new trust region algorithm for a nonlinear bilevel programming problem by solving a series of its linear or quadratic approximation subproblems.For the nonlinear bilevel programming problem in which the lower level programming problem is a strongly convex programming problem with linear constraints,we show that each accumulation point of the iterative sequence produced by this algorithm is a stationary point of the bilevel programming problem.
Plasmonics and the parallel programming problem
Vishkin, Uzi; Smolyaninov, Igor; Davis, Chris
2007-02-01
While many parallel computers have been built, it has generally been too difficult to program them. Now, all computers are effectively becoming parallel machines. Biannual doubling in the number of cores on a single chip, or faster, over the coming decade is planned by most computer vendors. Thus, the parallel programming problem is becoming more critical. The only known solution to the parallel programming problem in the theory of computer science is through a parallel algorithmic theory called PRAM. Unfortunately, some of the PRAM theory assumptions regarding the bandwidth between processors and memories did not properly reflect a parallel computer that could be built in previous decades. Reaching memories, or other processors in a multi-processor organization, required off-chip connections through pins on the boundary of each electric chip. Using the number of transistors that is becoming available on chip, on-chip architectures that adequately support the PRAM are becoming possible. However, the bandwidth of off-chip connections remains insufficient and the latency remains too high. This creates a bottleneck at the boundary of the chip for a PRAM-On-Chip architecture. This also prevents scalability to larger "supercomputing" organizations spanning across many processing chips that can handle massive amounts of data. Instead of connections through pins and wires, power-efficient CMOS-compatible on-chip conversion to plasmonic nanowaveguides is introduced for improved latency and bandwidth. Proper incorporation of our ideas offer exciting avenues to resolving the parallel programming problem, and an alternative way for building faster, more useable and much more compact supercomputers.
An Algorithm for Linearly Constrained Nonlinear Programming Programming Problems.
1980-01-01
ALGORITHM FOR LINEARLY CONSTRAINED NONLINEAR PROGRAMMING PROBLEMS Mokhtar S. Bazaraa and Jamie J. Goode In this paper an algorithm for solving a linearly...distance pro- gramr.ing, as in the works of Bazaraa and Goode 12], and Wolfe [16 can be used for solving this problem. Special methods that take advantage of...34 Pacific Journal of Mathematics, Volume 16, pp. 1-3, 1966. 2. M. S. Bazaraa and J. j. Goode, "An Algorithm for Finding the Shortest Element of a
On Quasi E-Convex Bilevel Programming Problem
Directory of Open Access Journals (Sweden)
E. A. Youness
2005-01-01
Full Text Available Bilevel programming problems involve two optimization problems where the data of the first one is implicity determined by the solution of the second. This study introduces the notions of E-convexity and quasi E-convexity in bilevel programming problems to generalize quasi convex bilevel programming problems.
Geometric optimal control of the contrast imaging problem in Nuclear Magnetic Resonance
Bonnard, B; Glaser, S J; Lapert, M; Sugny, D; Zhang, Y
2012-01-01
The objective of this article is to introduce the tools to analyze the contrast imaging problem in Nuclear Magnetic Resonance. Optimal trajectories can be selected among extremal solutions of the Pontryagin Maximum Principle applied to this Mayer type optimal problem. Such trajectories are associated to the question of extremizing the transfer time. Hence the optimal problem is reduced to the analysis of the Hamiltonian dynamics related to singular extremals and their optimality status. This is illustrated by using the examples of cerebrospinal fluid / water and grey / white matter of cerebrum.
Muniz Oliva, Waldyr
2002-01-01
Geometric Mechanics here means mechanics on a pseudo-riemannian manifold and the main goal is the study of some mechanical models and concepts, with emphasis on the intrinsic and geometric aspects arising in classical problems. The first seven chapters are written in the spirit of Newtonian Mechanics while the last two ones as well as two of the four appendices describe the foundations and some aspects of Special and General Relativity. All the material has a coordinate free presentation but, for the sake of motivation, many examples and exercises are included in order to exhibit the desirable flavor of physical applications.
Pallozzi Lavorante, Luca; Dirk Ebert, Hans
2008-07-01
Tensor3D is a geometric modeling program with the capacity to simulate and visualize in real-time the deformation, specified through a tensor matrix and applied to triangulated models representing geological bodies. 3D visualization allows the study of deformational processes that are traditionally conducted in 2D, such as simple and pure shears. Besides geometric objects that are immediately available in the program window, the program can read other models from disk, thus being able to import objects created with different open-source or proprietary programs. A strain ellipsoid and a bounding box are simultaneously shown and instantly deformed with the main object. The principal axes of strain are visualized as well to provide graphical information about the orientation of the tensor's normal components. The deformed models can also be saved, retrieved later and deformed again, in order to study different steps of progressive strain, or to make this data available to other programs. The shape of stress ellipsoids and the corresponding Mohr circles defined by any stress tensor can also be represented. The application was written using the Visualization ToolKit, a powerful scientific visualization library in the public domain. This development choice, allied to the use of the Tcl/Tk programming language, which is independent on the host computational platform, makes the program a useful tool for the study of geometric deformations directly in three dimensions in teaching as well as research activities.
Lu, Bao-Liang; Ito, Koji
2003-09-01
In this paper we present a method for converting general nonlinear programming (NLP) problems into separable programming (SP) problems by using feedforward neural networks (FNNs). The basic idea behind the method is to use two useful features of FNNs: their ability to approximate arbitrary continuous nonlinear functions with a desired degree of accuracy and their ability to express nonlinear functions in terms of parameterized compositions of functions of single variables. According to these two features, any nonseparable objective functions and/or constraints in NLP problems can be approximately expressed as separable functions with FNNs. Therefore, any NLP problems can be converted into SP problems. The proposed method has three prominent features. (a) It is more general than existing transformation techniques; (b) it can be used to formulate optimization problems as SP problems even when their precise analytic objective function and/or constraints are unknown; (c) the SP problems obtained by the proposed method may highly facilitate the selection of grid points for piecewise linear approximation of nonlinear functions. We analyze the computational complexity of the proposed method and compare it with an existing transformation approach. We also present several examples to demonstrate the method and the performance of the simplex method with the restricted basis entry rule for solving SP problems.
Fifth SIAM conference on geometric design 97: Final program and abstracts. Final technical report
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-12-31
The meeting was divided into the following sessions: (1) CAD/CAM; (2) Curve/Surface Design; (3) Geometric Algorithms; (4) Multiresolution Methods; (5) Robotics; (6) Solid Modeling; and (7) Visualization. This report contains the abstracts of papers presented at the meeting. Proceding the conference there was a short course entitled ``Wavelets for Geometric Modeling and Computer Graphics``.
AgentGeom: A Multiagent System for Pedagogical Support in Geometric Proof Problems
Cobo, Pedro; Fortuny, Josep M.; Puertas, Eloi; Richard, Philippe R.
2007-01-01
This paper aims, first, to describe the fundamental characteristics and workings of the AgentGeom artificial tutorial system, which is designed to help students develop knowledge and skills related to problem solving, mathematical proof in geometry, and the use of mathematical language. Following this, we indicate the manner in which a secondary…
Geometric characterization for the least Lagrangian action of n-body problems
Institute of Scientific and Technical Information of China (English)
张世清; 周青
2001-01-01
For n-body problems with quasihomogeneous potentials in Rk (2［n/2］≤k) we prove that the minimum of the Lagrangian action integral defined on the zero mean loop space is exactly the circles with center at the origin and the configuration of the n-bodies is always a regular n-1 simplex with fixed side length.
Report on Workshop on Geometric Scattering
DEFF Research Database (Denmark)
As part of the activities of MaPhySto a workshop on geometric scattering was organized at University of Aarhus, November 5-7, 1998. The workshop was narrowly focused on geometric scattering, and in particular the use of geometric scattering in understanding the structure of the scattering operator...... for the quantum mechanical many-body problem. A number of other questions were also discussed in detail, including the resonances and various geometric questions. This report includes the program of the workshop, a collection of previews, abstracts, and reports on the lectures, with extensive references....
Mitchell, Lawrence
2016-01-01
The implementation of efficient multigrid preconditioners for elliptic partial differential equations (PDEs) is a challenge due to the complexity of the resulting algorithms and corresponding computer code. For sophisticated finite element discretisations on unstructured grids an efficient implementation can be very time consuming and requires the programmer to have in-depth knowledge of the mathematical theory, parallel computing and optimisation techniques on manycore CPUs. In this paper we show how the development of bespoke multigrid preconditioners can be simplified significantly by using a framework which allows the expression of the each component of the algorithm at the correct abstraction level. Our approach (1) allows the expression of the finite element problem in a language which is close to the mathematical formulation of the problem, (2) guarantees the automatic generation and efficient execution of parallel optimised low-level computer code and (3) is flexible enough to support different abstra...
Aydin, Umit; Dogrusoz, Yesim Serinagaoglu
2011-09-01
In this article, we aimed to reduce the effects of geometric errors and measurement noise on the inverse problem of Electrocardiography (ECG) solutions. We used the Kalman filter to solve the inverse problem in terms of epicardial potential distributions. The geometric errors were introduced into the problem via wrong determination of the size and location of the heart in simulations. An error model, which is called the enhanced error model (EEM), was modified to be used in inverse problem of ECG to compensate for the geometric errors. In this model, the geometric errors are modeled as additive Gaussian noise and their noise variance is added to the measurement noise variance. The Kalman filter method includes a process noise component, whose variance should also be estimated along with the measurement noise. To estimate these two noise variances, two different algorithms were used: (1) an algorithm based on residuals, (2) expectation maximization algorithm. The results showed that it is important to use the correct noise variances to obtain accurate results. The geometric errors, if ignored in the inverse solution procedure, yielded incorrect epicardial potential distributions. However, even with a noise model as simple as the EEM, the solutions could be significantly improved.
Curvature and geodesic instabilities in a geometrical approach to the planar three-body problem
Krishnaswami, Govind S.; Senapati, Himalaya
2016-10-01
The Maupertuis principle allows us to regard classical trajectories as reparametrized geodesics of the Jacobi-Maupertuis (JM) metric on configuration space. We study this geodesic reformulation of the planar three-body problem with both Newtonian and attractive inverse-square potentials. The associated JM metrics possess translation and rotation isometries in addition to scaling isometries for the inverse-square potential with zero energy E. The geodesic flow on the full configuration space ℂ3 (with collision points excluded) leads to corresponding flows on its Riemannian quotients: the center of mass configuration space ℂ2 and shape space ℝ3 (as well as 𝕊3 and the shape sphere 𝕊2 for the inverse-square potential when E = 0). The corresponding Riemannian submersions are described explicitly in "Hopf" coordinates which are particularly adapted to the isometries. For equal masses subject to inverse-square potentials, Montgomery shows that the zero-energy "pair of pants" JM metric on the shape sphere is geodesically complete and has negative gaussian curvature except at Lagrange points. We extend this to a proof of boundedness and strict negativity of scalar curvatures everywhere on ℂ2, ℝ3, and 𝕊3 with collision points removed. Sectional curvatures are also found to be largely negative, indicating widespread geodesic instabilities. We obtain asymptotic metrics near collisions, show that scalar curvatures have finite limits, and observe that the geodesic reformulation "regularizes" pairwise and triple collisions on ℂ2 and its quotients for arbitrary masses and allowed energies. For the Newtonian potential with equal masses and zero energy, we find that the scalar curvature on ℂ2 is strictly negative though it could have either sign on ℝ3. However, unlike for the inverse-square potential, geodesics can encounter curvature singularities at collisions in finite geodesic time.
Lenarda, P; Paggi, M
A comprehensive computational framework based on the finite element method for the simulation of coupled hygro-thermo-mechanical problems in photovoltaic laminates is herein proposed. While the thermo-mechanical problem takes place in the three-dimensional space of the laminate, moisture diffusion occurs in a two-dimensional domain represented by the polymeric layers and by the vertical channel cracks in the solar cells. Therefore, a geometrical multi-scale solution strategy is pursued by solving the partial differential equations governing heat transfer and thermo-elasticity in the three-dimensional space, and the partial differential equation for moisture diffusion in the two dimensional domains. By exploiting a staggered scheme, the thermo-mechanical problem is solved first via a fully implicit solution scheme in space and time, with a specific treatment of the polymeric layers as zero-thickness interfaces whose constitutive response is governed by a novel thermo-visco-elastic cohesive zone model based on fractional calculus. Temperature and relative displacements along the domains where moisture diffusion takes place are then projected to the finite element model of diffusion, coupled with the thermo-mechanical problem by the temperature and crack opening dependent diffusion coefficient. The application of the proposed method to photovoltaic modules pinpoints two important physical aspects: (i) moisture diffusion in humidity freeze tests with a temperature dependent diffusivity is a much slower process than in the case of a constant diffusion coefficient; (ii) channel cracks through Silicon solar cells significantly enhance moisture diffusion and electric degradation, as confirmed by experimental tests.
Lenarda, P.; Paggi, M.
2016-06-01
A comprehensive computational framework based on the finite element method for the simulation of coupled hygro-thermo-mechanical problems in photovoltaic laminates is herein proposed. While the thermo-mechanical problem takes place in the three-dimensional space of the laminate, moisture diffusion occurs in a two-dimensional domain represented by the polymeric layers and by the vertical channel cracks in the solar cells. Therefore, a geometrical multi-scale solution strategy is pursued by solving the partial differential equations governing heat transfer and thermo-elasticity in the three-dimensional space, and the partial differential equation for moisture diffusion in the two dimensional domains. By exploiting a staggered scheme, the thermo-mechanical problem is solved first via a fully implicit solution scheme in space and time, with a specific treatment of the polymeric layers as zero-thickness interfaces whose constitutive response is governed by a novel thermo-visco-elastic cohesive zone model based on fractional calculus. Temperature and relative displacements along the domains where moisture diffusion takes place are then projected to the finite element model of diffusion, coupled with the thermo-mechanical problem by the temperature and crack opening dependent diffusion coefficient. The application of the proposed method to photovoltaic modules pinpoints two important physical aspects: (i) moisture diffusion in humidity freeze tests with a temperature dependent diffusivity is a much slower process than in the case of a constant diffusion coefficient; (ii) channel cracks through Silicon solar cells significantly enhance moisture diffusion and electric degradation, as confirmed by experimental tests.
Method for solving a convex integer programming problem
Stefanov, Stefan M.
2003-01-01
We consider a convex integer program which is a nonlinear version of the assignment problem. This problem is reformulated as an equivalent problem. An algorithm for solving the original problem is suggested which is based on solving the simple assignment problem via some of known algorithms.
Geometric constraint solving with geometric transformation
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
This paper proposes two algorithms for solving geometric constraint systems. The first algorithm is for constrained systems without loops and has linear complexity. The second algorithm can solve constraint systems with loops. The latter algorithm is of quadratic complexity and is complete for constraint problems about simple polygons. The key to it is to combine the idea of graph based methods for geometric constraint solving and geometric transformations coming from rule-based methods.
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
The Uniqueness of Optimal Solution for Linear Programming Problem
Institute of Scientific and Technical Information of China (English)
QuanlingWei; HongYan; JunWang
2004-01-01
This paper investigates an old problem in operations research, the uniqueness of the optimal solution to a linear programming problem. We discuss the problem on a general polyhedron, give some equivalent conditions for uniqueness testing. In addition, we discuss the implementation issues for linear programming based decision making procedures,which motivated this research.
Some Duality Results for Fuzzy Nonlinear Programming Problem
Sangeeta Jaiswal; Geetanjali Panda
2012-01-01
The concept of duality plays an important role in optimization theory. This paper discusses some relations between primal and dual nonlinear programming problems in fuzzy environment. Here, fuzzy feasible region for a general fuzzy nonlinear programming is formed and the concept of fuzzy feasible solution is defined. First order dual relation for fuzzy nonlinear programming problem is studied.
Bilevel programming problems theory, algorithms and applications to energy networks
Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya
2015-01-01
This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.
Optimal impulse control problems and linear programming.
Bauso, D.
2009-01-01
Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, ...
Zangiabadi, M.; H. R. MALEKI
2007-01-01
In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
Institute of Scientific and Technical Information of China (English)
康盛亮
2001-01-01
Using the modified method of multiple scales, the nonlinear stability of a truncated shallow spherical shell of variable thickness with a nondeformable rigid body at the center under compound loads is investigated. When the geometrical parameter k is larger,the uniformly valid asymptotic solutions of this problem are obtained and the remainder terms are estimated.
Bi-Objective Bilevel Programming Problem: A Fuzzy Approach
Directory of Open Access Journals (Sweden)
Haseen S.
2015-12-01
Full Text Available In this paper, a likely situation of a set of decision maker’s with bi-objectives in case of fuzzy multi-choice goal programming is considered. The problem is then carefully formulated as a bi-objective bilevel programming problem (BOBPP with multiple fuzzy aspiration goals, fuzzy cost coefficients and fuzzy decision variables. Using Ranking method the fuzzy bi-objective bilevel programming problem (FBOBPP is converted into a crisp model. The transformed problem is further solved by adopting a two level Stackelberg game theory and fuzzy decision model of Sakawa. A numerical with hypothetical values is also used to illustrate the problem.
A program to solve rotating plasma problems
Bakker, M.; Berg, M.S. van den
1980-01-01
It is shown that the solution of a rotating plasma problem minimizes a quitably chosen funtional. This variational problem is solved by the Ritz-Galerkin methud using piecewise bilinear functions and applying some Newton-Côtes-like quadrature. The resulting linear system with a sparse nonegative def
Constraint-based scheduling applying constraint programming to scheduling problems
Baptiste, Philippe; Nuijten, Wim
2001-01-01
Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...
Directory of Open Access Journals (Sweden)
Velibor V Vujović
2011-01-01
Full Text Available This paper presents the algorithm and results of a computer program for calculation of complex equilibrium composition for the high temperature fossil fuel combustion products. The method of determining the composition of high temperatures combustion products at the temperatures appearing in the open cycle MHD power generation is given. The determination of combustion product composition is based on minimization of the Gibbs free energy. The number of equations to be solved is reduced by using variational principles and a method of geometric programming and is equal to the sum of the numbers of elements and phases. A short description of the computer program for the calculation of the composition and an example of the results are also given.
Acevedo Pardo, Carlos; Farjas Abadía, Mercedes; Georgopoulos, Andreas; Obuchovski, Romuald; Parenti, Roberto; Paršeliūnas, Eimuntas Kazimieras; Rodríguez Miranda, Álvaro; Schramm, Thomas; Valle Melón, José Manuel; Zazo Ferreras, Arturo; Apanavičiūtė, Asta; Arrighetti, Andrea; Auskalnis, Vytautas; Bergmann, Lukas; Bregianni, Angeliki
2011-01-01
[EN] Data contained in this record come from the following accademic activity (from which it is possible to locate additional records related with the Monastery): ● LDGP_inv_002: "Intensive Program ERASMUS: TOPCART. Geometric Documentation of the Heritage (administrative and academic documentation)", http://hdl.handle.net/10810/9906 [ES] Los datos de este registro provienen de la una actividad académica que también aparece descrita en el repositorio y desde donde se puede acceder a otro...
Improve Problem Solving Skills through Adapting Programming Tools
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
Improve Problem Solving Skills through Adapting Programming Tools
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
Multiobjective Interaction Programming Problem with Interaction Constraint for Two Players
Directory of Open Access Journals (Sweden)
Min Jiang
2012-01-01
Full Text Available This paper extends an existing cooperative multi-objective interaction programming problem with interaction constraint for two players (or two agents. First, we define an s-optimal joint solution with weight vector to multi-objective interaction programming problem with interaction constraint for two players and get some properties of it. It is proved that the s-optimal joint solution with weight vector to the multi-objective interaction programming problem can be obtained by solving a corresponding mathematical programming problem. Then, we define another s-optimal joint solution with weight value to multi-objective interaction programming problem with interaction constraint for two players and get some of its properties. It is proved that the s-optimal joint solution with weight vector to multi-objective interaction programming problem can be obtained by solving a corresponding mathematical programming problem. Finally, we build a pricing multi-objective interaction programming model for a bi-level supply chain. Numerical results show that the interaction programming pricing model is better than Stackelberg pricing model and the joint pricing model.
DNA computation model to solve 0-1 programming problem.
Zhang, Fengyue; Yin, Zhixiang; Liu, Bo; Xu, Jin
2004-01-01
0-1 programming problem is an important problem in opsearch with very widespread applications. In this paper, a new DNA computation model utilizing solution-based and surface-based methods is presented to solve the 0-1 programming problem. This model contains the major benefits of both solution-based and surface-based methods; including vast parallelism, extraordinary information density and ease of operation. The result, verified by biological experimentation, revealed the potential of DNA computation in solving complex programming problem.
Kim, SugHee; Chung, KwangSik; Yu, HeonChang
2013-01-01
The purpose of this paper is to propose a training program for creative problem solving based on computer programming. The proposed program will encourage students to solve real-life problems through a creative thinking spiral related to cognitive skills with computer programming. With the goal of enhancing digital fluency through this proposed…
An Interval Maximum Entropy Method for Quadratic Programming Problem
Institute of Scientific and Technical Information of China (English)
RUI Wen-juan; CAO De-xin; SONG Xie-wu
2005-01-01
With the idea of maximum entropy function and penalty function methods, we transform the quadratic programming problem into an unconstrained differentiable optimization problem, discuss the interval extension of the maximum entropy function, provide the region deletion test rules and design an interval maximum entropy algorithm for quadratic programming problem. The convergence of the method is proved and numerical results are presented. Both theoretical and numerical results show that the method is reliable and efficient.
PROGRAMMING OF METHODS FOR THE NEEDS OF LOGISTICS DISTRIBUTION SOLVING PROBLEMS
Directory of Open Access Journals (Sweden)
Andrea Štangová
2014-06-01
Full Text Available Logistics has become one of the dominant factors which is affecting the successful management, competitiveness and mentality of the global economy. Distribution logistics materializes the connesciton of production and consumer marke. It uses different methodology and methods of multicriterial evaluation and allocation. This thesis adresses the problem of the costs of securing the distribution of product. It was therefore relevant to design a software product thet would be helpful in solvin the problems related to distribution logistics. Elodis – electronic distribution logistics program was designed on the basis of theoretical analysis of the issue of distribution logistics and on the analysis of the software products market. The program uses a multicriterial evaluation methods to deremine the appropriate type and mathematical and geometrical method to determine an appropriate allocation of the distribution center, warehouse and company.
Chaotic Neural Network Technique for "0-1" Programming Problems
Institute of Scientific and Technical Information of China (English)
王秀宏; 乔清理; 王正欧
2003-01-01
0-1 programming is a special case of the integer programming, which is commonly encountered in many optimization problems. Neural network and its general energy function are presented for 0-1 optimization problem. Then,the 0-1 optimization problems are solved by a neural network model with transient chaotic dynamics (TCNN). Numerical simulations of two typical 0-1 optimization problems show that TCNN can overcome HNN's main drawbacks that it suffers from the local minimum and can search for the global optimal solutions in to solveing 0-1 optimization problems.
Evolutionary Programming for IP/MIP Problems with Linear Constraints
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
In this paper, we propose a modified evolutionary programming with dynamic domain for solving nonlinear IP/MIP problems with linear constraints, without involving penalty function or any transformation for the problem to a linear model or others. The numerical results show that the new algorithm gives a satisfactory performance in which it works of high speed and accuracy in IP/MIP problems.
Refinement from a control problem to program
DEFF Research Database (Denmark)
Schenke, Michael; Ravn, Anders P.
1996-01-01
for a control task, exemplified by a steam boiler.The same formalism is used to refine requirements to a functional design.Through a suitable transformation this is taken to an event andaction based formalism. Finally components in this design for a distributedarchitecture are transformed to occam-like programs....
Directory of Open Access Journals (Sweden)
Luciano Boi
2004-07-01
Full Text Available We study the role of geometrical and topological concepts in the recent developments of theoretical physics, notably in non-Abelian gauge theories and superstring theory, and further we show the great significance of these concepts for a deeper understanding of the dynamical laws of physics. This work aims to demonstrate that the global topological properties of the manifold's model of spacetime play a major role in quantum field theory and that, therefore, several physical quantum effects arise from the nonlocal metrical and topological structure of this manifold. We mathematically argue the need for building new structures of space with different topology. This means, in particular, that the Ã‚Â“hiddenÃ‚Â” symmetries of fundamental physics can be related to the phenomenon of topological change of certain classes of (presumably nonsmooth manifolds.
Quasi-Topological Gauged Sigma Models, The Geometric Langlands Program, And Knots
Tan, Meng-Chwan
2011-01-01
We construct and study a closed, two-dimensional, quasi-topological (0,2) gauged sigma model with target space a smooth G-manifold, where G is any compact and connected Lie group. When the target space is a flag manifold of simple G, and the gauge group is a Cartan subgroup thereof, the perturbative model describes, purely physically, the recently formulated mathematical theory of "Twisted Chiral Differential Operators". This paves the way, via a generalized T-duality, for a natural physical interpretation of the geometric Langlands correspondence for simply-connected, simple, complex Lie groups. In particular, the Hecke eigensheaves and Hecke operators can be described in terms of the correlation functions of certain operators that underlie the infinite-dimensional chiral algebra of the flag manifold model. Nevertheless, nonperturbative worldsheet twisted-instantons can, in some situations, trivialize the chiral algebra completely. This leads to a spontaneous breaking of supersymmetry whilst implying certain...
An Adaptive Neural Network Model for Nonlinear Programming Problems
Institute of Scientific and Technical Information of China (English)
Xiang-sun Zhang; Xin-jian Zhuo; Zhu-jun Jing
2002-01-01
In this paper a canonical neural network with adaptively changing synaptic weights and activation function parameters is presented to solve general nonlinear programming problems. The basic part of the model is a sub-network used to find a solution of quadratic programming problems with simple upper and lower bounds. By sequentially activating the sub-network under the control of an external computer or a special analog or digital processor that adjusts the weights and parameters, one then solves general nonlinear programming problems. Convergence proof and numerical results are given.
On semidefinite programming relaxations of the traveling salesman problem
de Klerk, Etienne; Sotirov, Renata; 10.1137/070711141
2009-01-01
We consider a new semidefinite programming (SDP) relaxation of the symmetric traveling salesman problem (TSP) that may be obtained via an SDP relaxation of the more general quadratic assignment problem (QAP). We show that the new relaxation dominates the one in [D. Cvetkovic, M. Cangalovic, and V. Kovacevic-Vujcic, Semidefinite programming methods for the symmetric traveling salesman problem, in Proc. 7th Int. IPCO Conference, Springer, London, 1999, pp. 126--136]. Unlike the bound of Cvetkovic et al., the new SDP bound is not dominated by the Held-Karp linear programming bound, or vice versa.
A computer program to determine geometric parameters for the AFM solar arrays
Gaddy, E. M.
1974-01-01
A computer program has been written to aid in the design of the A. E. M.-1 solar array and to determine the power that will finally be available from the array. The program will plot the array output as a function of the satellite's position in a given orbit and will calculate the average output over the orbit.
Geochemical engineering problem identification and program description. Final report
Energy Technology Data Exchange (ETDEWEB)
Crane, C.H.; Kenkeremath, D.C.
1981-05-01
The Geochemical Engineering Program has as its goal the improvement of geochemical fluid management techniques. This document presents the strategy and status of the Geochemical Engineering Program. The magnitude and scope of geochemical-related problems constraining geothermal industry productivity are described. The goals and objectives of the DGE Geochemical Engineering Program are defined. The rationale and strategy of the program are described. The structure, priorities, funding, and management of specific elements within the program are delineated, and the status of the overall program is presented.
Matlab A Practical Introduction to Programming and Problem Solving
Attaway, Stormy
2011-01-01
Assuming no knowledge of programming, this book presents both programming concepts and MATLAB's built-in functions, providing a perfect platform for exploiting MATLAB's extensive capabilities for tackling engineering problems. It starts with programming concepts such as variables, assignments, input/output, and selection statements, moves onto loops and then solves problems using both the 'programming concept' and the 'power of MATLAB' side-by-side. In-depth coverage is given to input/output, a topic that is fundamental to many engineering applications. Ancillaries available with the text: I
Measurement problem in Program Universe. Revision
Energy Technology Data Exchange (ETDEWEB)
Noyes, H.P.; Gefwert, C.; Manthey, M.J.
1985-07-01
The ''measurement problem'' of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not ''and'') G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact. 15 refs.
Measurement problem in Program Universe. Revision
Noyes, H. P.; Gefwert, C.; Manthey, M. J.
1985-07-01
The measurement problem of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not and) G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.
An approach for solving linear fractional programming problems ...
African Journals Online (AJOL)
An approach for solving linear fractional programming problems. ... Journal of the Nigerian Association of Mathematical Physics. Journal Home · ABOUT · Advanced Search ... Open Access DOWNLOAD FULL TEXT Subscription or Fee Access ...
The Environmental Justice Collaborative Problem-Solving Cooperative Agreement Program
The Environmental Justice Collaborative Problem-Solving (CPS) Cooperative Agreement Program provides financial assistance to eligible organizations working on or planning to work on projects to address local environmental and/or public health issues
A Hybrid Dynamic Programming Method for Concave Resource Allocation Problems
Institute of Scientific and Technical Information of China (English)
姜计荣; 孙小玲
2005-01-01
Concave resource allocation problem is an integer programming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the revised domain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
Linear Programming and Its Application to Pattern Recognition Problems
Omalley, M. J.
1973-01-01
Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.
Solving linear integer programming problems by a novel neural model.
Cavalieri, S
1999-02-01
The paper deals with integer linear programming problems. As is well known, these are extremely complex problems, even when the number of integer variables is quite low. Literature provides examples of various methods to solve such problems, some of which are of a heuristic nature. This paper proposes an alternative strategy based on the Hopfield neural network. The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems, including well-known problems such as the Travelling Salesman Problem and the Set Covering Problem. After a brief description of this class of problems, it is demonstrated that the original Hopfield model is incapable of supplying valid solutions. This is attributed to the presence of constant bias currents in the dynamic of the neural model. A demonstration of this is given and then a novel neural model is presented which continues to be based on the same architecture as the Hopfield model, but introduces modifications thanks to which the integer linear programming problems presented can be solved. Some numerical examples and concluding remarks highlight the solving capacity of the novel neural model.
Solving quadratic programming problems by delayed projection neural network.
Yang, Yongqing; Cao, Jinde
2006-11-01
In this letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network.
Problems in Choosing Tools and Methods for Teaching Programming
Vitkute-Adžgauskiene, Davia; Vidžiunas, Antanas
2012-01-01
The paper analyses the problems in selecting and integrating tools for delivering basic programming knowledge at the university level. Discussion and analysis of teaching the programming disciplines, the main principles of study programme design, requirements for teaching tools, methods and corresponding languages is presented, based on literature…
Using Problem Solving to Teach a Programming Language.
Milbrandt, George
1995-01-01
Computer studies courses should incorporate as many computer concepts and programming language experiences as possible. A gradual increase in problem difficulty will help the student to understand various computer concepts, and the programming language's syntax and structure. A sidebar provides two examples of how to establish a learning…
Efficient numerical methods for entropy-linear programming problems
Gasnikov, A. V.; Gasnikova, E. B.; Nesterov, Yu. E.; Chernov, A. V.
2016-04-01
Entropy-linear programming (ELP) problems arise in various applications. They are usually written as the maximization of entropy (minimization of minus entropy) under affine constraints. In this work, new numerical methods for solving ELP problems are proposed. Sharp estimates for the convergence rates of the proposed methods are established. The approach described applies to a broader class of minimization problems for strongly convex functionals with affine constraints.
METHOD OF CENTERS ALGORITHM FOR MULTI-OBJECTIVE PROGRAMMING PROBLEMS
Institute of Scientific and Technical Information of China (English)
Tarek Emam
2009-01-01
In this paper, we consider a method of centers for solving multi-objective programming problems, where the objective functions involved are concave functions and the set of feasible points is convex. The algorithm is defined so that the sub-problems that must be solved during its execution may be solved by finite-step procedures. Conditions are given under which the algorithm generates sequences of feasible points and constraint multiplier vectors that have accumulation points satisfying the KKT conditions. Finally, we establish convergence of the proposed method of centers algorithm for solving multiobjective programming problems.
EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.
Jarvis, John J.; And Others
Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…
Linear decomposition approach for a class of nonconvex programming problems.
Shen, Peiping; Wang, Chunfeng
2017-01-01
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
An adaptive genetic algorithm for solving bilevel linear programming problem
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems.Various methods are proposed for solving this problem. Of all the algorithms, the genetic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes may be infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references.
Geometric Computing Based on Computerized Descriptive Geometric
Institute of Scientific and Technical Information of China (English)
YU Hai-yan; HE Yuan-Jun
2011-01-01
Computer-aided Design （CAD）, video games and other computer graphic related technology evolves substantial processing to geometric elements. A novel geometric computing method is proposed with the integration of descriptive geometry, math and computer algorithm. Firstly, geometric elements in general position are transformed to a special position in new coordinate system. Then a 3D problem is projected to new coordinate planes. Finally, according to 2D/3D correspondence principle in descriptive geometry, the solution is constructed computerized drawing process with ruler and compasses. In order to make this method a regular operation, a two-level pattern is established. Basic Layer is a set algebraic packaged function including about ten Primary Geometric Functions （PGF） and one projection transformation. In Application Layer, a proper coordinate is established and a sequence of PGFs is sought for to get the final results. Examples illustrate the advantages of our method on dimension reduction, regulatory and visual computing and robustness.
The geometric effect and programming current reduction in cylindrical-shaped phase change memory
Li, Yiming; Hwang, Chih-Hong; Li, Tien-Yeh; Cheng, Hui-Wen
2009-07-01
This study conducts a three-dimensional electro-thermal time-domain simulation for numerical analysis of cylindrical-shaped phase change memories (PCMs). The influence of chalcogenide material, germanium antimony telluride (GeSbTe or GST), structure on PCM operation is explored. GST with vertical structure exhibits promising characteristics. The bottom electrode contact (BEC) is advanced to improve the operation of PCMs, where a 25% reduction of the required programming current is achieved at a cost of 26% reduced resistance ratio. The position of the BEC is then shifted to further improve the performance of PCMs. The required programming current is reduced by a factor of 11, where the resistance ratio is only decreased by 6.9%. However, the PCMs with a larger shift of BEC are sensitive to process variation. To design PCMs with less than 10% programming current variation, PCMs with shifted BEC, where the shifted distance is equal to 1.5 times the BEC's radius, is worth considering. This study quantitatively estimates the structure effect on the phase transition of PCMs and physically provides an insight into the design and technology of PCMs.
Mathematical programming methods for large-scale topology optimization problems
DEFF Research Database (Denmark)
Rojas Labanda, Susana
, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second......This thesis investigates new optimization methods for structural topology optimization problems. The aim of topology optimization is finding the optimal design of a structure. The physical problem is modelled as a nonlinear optimization problem. This powerful tool was initially developed...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...
Bonus algorithm for large scale stochastic nonlinear programming problems
Diwekar, Urmila
2015-01-01
This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these ...
Solving Classification Problems Using Genetic Programming Algorithms on GPUs
Cano, Alberto; Zafra, Amelia; Ventura, Sebastián
Genetic Programming is very efficient in problem solving compared to other proposals but its performance is very slow when the size of the data increases. This paper proposes a model for multi-threaded Genetic Programming classification evaluation using a NVIDIA CUDA GPUs programming model to parallelize the evaluation phase and reduce computational time. Three different well-known Genetic Programming classification algorithms are evaluated using the parallel evaluation model proposed. Experimental results using UCI Machine Learning data sets compare the performance of the three classification algorithms in single and multithreaded Java, C and CUDA GPU code. Results show that our proposal is much more efficient.
Recognition of geometric primitives using logic-program and probabilistic-network reasoning methods
Munck-Fairwood, Roger C.
1992-03-01
This paper addresses the issue of recognition of 3-D objects from a potentially very large database of categories of objects, assuming the data are provided in the form of the edges available from a single monocular view, which indicate the discontinuities in depth and surface orientation. The work is partly inspired by the `Recognition by Components' approach suggested fairly recently by Irving Biederman using `geons,' chosen for their qualitatively distinguishable nonmetric viewpoint-invariant properties. The work is also inspired by Richard Gregory's model of human visual recognition which involves probabilistic reasoning, and the regarding of perception as hypothesis. Further, the interpretation of some data can influence the expectation of other data. A novel attempt is made here to apply two automatic reasoning tools to a sub-task of the general recognition process, viz., the recognition of isolated geons in an idealized image. The tools are logic programming and `belief networks' (causal probabilistic networks). Both the tools have the important property of allowing propagation of information in both directions, i.e., data to hypotheses, and vice-versa. The results to date show good patterns of reasoning consistent with one's intuition and point to the possibility of appropriately `tuning' some feature detectors according to other data received. Future goals include the recognition of geons from real gray-level image data, the extension of the belief network to composite objects, and the use of a reverse-driven image analysis logic program to generate graphics and thereby identify appropriate model constraints.
M Sakawa; Kato, K.
2009-01-01
This paper considers stochastic two-level linear programming problems. Using the concept of chance constraints and probability maximization, original problems are transformed into deterministic ones. An interactive fuzzy programming method is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance.
Domínguez, Luis F.
2010-12-01
This work introduces two algorithms for the solution of pure integer and mixed-integer bilevel programming problems by multiparametric programming techniques. The first algorithm addresses the integer case of the bilevel programming problem where integer variables of the outer optimization problem appear in linear or polynomial form in the inner problem. The algorithm employs global optimization techniques to convexify nonlinear terms generated by a reformulation linearization technique (RLT). A continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem appear in linear or polynomial forms in the inner problem. The algorithm relies on the use of global multiparametric mixed-integer programming techniques at the inner optimization level. In both algorithms, the multiparametric solutions obtained are embedded in the outer problem to form a set of single-level (M)(I)(N)LP problems - which are then solved to global optimality using standard fixed-point (global) optimization methods. Numerical examples drawn from the open literature are presented to illustrate the proposed algorithms. © 2010 Elsevier Ltd.
A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems
Tunjo Perić; Zoran Babić; Sead Rešić
2014-01-01
This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP) problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.
A new heuristic algorithm for general integer linear programming problems
Institute of Scientific and Technical Information of China (English)
GAO Pei-wang; CAI Ying
2006-01-01
A new heuristic algorithm is proposed for solving general integer linear programming problems.In the algorithm,the objective function hyperplane is used as a cutting plane,and then by introducing a special set of assistant sets,an efficient heuristic search for the solution to the integer linear program is carried out in the sets on the objective function hyperplane.A simple numerical example shows that the algorithm is efficient for some problems,and therefore,of practical interest.
Quadratic growth and stability in convex programming problems
Bonnans, J. Frederic; Ioffe, Alexander D.
1994-01-01
Projet PROMATH; Given a convex program with $C^2$ functions and a convex set $S$ of solutions to the problem, we give a second order condition which guarantees that the problem does not have solutions outside of $S$. This condition is interpreted as a characterization for the quadratic growth of the cost function. The crucial role in the proofs is played by a theorem describing a certain uniform regularity property of critical cones in smooth convex programs. We apply these results to the dis...
Complexity of Data Dependence problems for Program Schemas with Concurrency
Danicic, Sebastian; Laurence, Michael R
2010-01-01
The problem of deciding whether one point in a program is data dependent upon another is fundamental to program analysis and has been widely studied. In this paper we consider this problem at the abstraction level of program schemas, in which computations occur in the Herbrand domain of terms and predicate symbols, which represent arbitrary predicate functions, are allowed. Given a vertex l in the flowchart of a schema S having only equality assignments and variables v,w, we show that it is PSPACE-hard to decide whether there exists an execution of a program defined by S in which v holds the initial value of w at at least one occurrence of l on the path of execution, with membership in PSPACE holding provided there is a constant upper bound on the arity of any predicate in S. We also consider the `dual' problem in which v is required to hold the initial value of w at every occurrence of l, for which the analogous results hold. Additionally, the former problem for programs with non-deterministic branching (in ...
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Energy Technology Data Exchange (ETDEWEB)
Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
Modified Filled Function to Solve NonlinearProgramming Problem
Institute of Scientific and Technical Information of China (English)
2015-01-01
Filled function method is an approach to find the global minimum of nonlinear functions. Many Problems, such as computing,communication control, and management, in real applications naturally result in global optimization formulations in a form ofnonlinear global integer programming. This paper gives a modified filled function method to solve the nonlinear global integerprogramming problem. The properties of the proposed modified filled function are also discussed in this paper. The results ofpreliminary numerical experiments are also reported.
Geometrical Bioelectrodynamics
Ivancevic, Vladimir G
2008-01-01
This paper proposes rigorous geometrical treatment of bioelectrodynamics, underpinning two fast-growing biomedical research fields: bioelectromagnetism, which deals with the ability of life to produce its own electromagnetism, and bioelectromagnetics, which deals with the effect on life from external electromagnetism. Keywords: Bioelectrodynamics, exterior geometrical machinery, Dirac-Feynman quantum electrodynamics, functional electrical stimulation
Modelling dynamic programming problems by generalized d-graphs
Kátai, Zoltán
2010-01-01
In this paper we introduce the concept of generalized d-graph (admitting cycles) as special dependency-graphs for modelling dynamic programming (DP) problems. We describe the d-graph versions of three famous single-source shortest algorithms (The algorithm based on the topological order of the vertices, Dijkstra algorithm and Bellman-Ford algorithm), which can be viewed as general DP strategies in the case of three different class of optimization problems. The new modelling method also makes possible to classify DP problems and the corresponding DP strategies in term of graph theory.
Managing problem employees: a model program and practical guide.
Miller, Laurence
2010-01-01
This article presents a model program for managing problem employees that includes a description ofthe basic types of problem employees and employee problems, as well as practical recommendations for. (1) selection and screening, (2) education and training, (3) coaching and counseling, (4) discipline, (5) psychological fitness-for-duty evaluations, (6) mental health services, (7) termination, and (8) leadership and administrative strategies. Throughout, the emphasis on balancing the need for order and productivity in the workplace with fairness and concern for employee health and well-being.
Longuski, James M.; Mcronald, Angus D.
1988-01-01
In previous work the problem of injecting the Galileo and Ulysses spacecraft from low earth orbit into their respective interplanetary trajectories has been discussed for the single stage (Centaur) vehicle. The central issue, in the event of spherically distributed injection errors, is what happens to the vehicle? The difficulties addressed in this paper involve the multi-stage problem since both Galileo and Ulysses will be utilizing the two-stage IUS system. Ulysses will also include a third stage: the PAM-S. The solution is expressed in terms of probabilities for total percentage of escape, orbit decay and reentry trajectories. Analytic solutions are found for Hill's Equations of Relative Motion (more recently called Clohessy-Wiltshire Equations) for multi-stage injections. These solutions are interpreted geometrically on the injection sphere. The analytic-geometric models compare well with numerical solutions, provide insight into the behavior of trajectories mapped on the injection sphere and simplify the numerical two-dimensional search for trajectory families.
An Interdisciplinary Program in Technical Communications: Problems Encountered.
Eckman, Martha
The need for experts in technical communication is growing significantly while the number of college graduates in the field accounts for less than one percent of the need. Three major types of problems should be considered in trying to establish a technical communication program: those involving society's need for better technical communicators,…
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
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Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
Alaska Problem Resource Manual: Alaska Future Problem Solving Program. Alaska Problem 1985-86.
Gorsuch, Marjorie, Ed.
"Alaska's Image in the Lower 48," is the theme selected by a Blue Ribbon panel of state and national leaders who felt that it was important for students to explore the relationship between Alaska's outside image and the effect of that image on the federal programs/policies that impact Alaska. An overview of Alaska is presented first in…
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Trunev A. P.
2014-05-01
Full Text Available In this article we have investigated the solutions of Maxwell's equations, Navier-Stokes equations and the Schrödinger associated with the solutions of Einstein's equations for empty space. It is shown that in some cases the geometric instability leading to turbulence on the mechanism of alternating viscosity, which offered by N.N. Yanenko. The mechanism of generation of matter from dark energy due to the geometric turbulence in the Big Bang has been discussed
PRIORITY PROGRAM OF UNEMPLOYMENT PROBLEM SOLVING IN PATI REGENCY
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Erni Arivia Arivia Roseline
2017-06-01
Full Text Available Pati is one regency that has the population with labor problems that is unemployment, and in 2013 Pati is a regency / city in Central Java with the fourth rank of unemployment rate. This research aims to make some program alternatives and to determine which alternative program that can be prioritized by the Government of Pati Regency in reducing the unemployment rate. The research uses the primary and secondary data. The analytical method used is Analysis Hierarchy Process (AHP and it is processed using the expert choice version 9.0. The result of research indicates that the efforts to reduce the unemployment rate in Pati Regency can be prioritized on the criterion: (1 empowering the people, and followed by (2 the capital from the investors, and (3 the empowerment of economic business. And the priority scale from the entire program alternatives of unemployment problem solving is a program to improve the rural community empowerment. The advice that can be given from this research is that the Government of Pati Regency should continuously conduct the job training and coaching to improve the quality and skills of the labors and also should increase the job opportunities, and also should improve and perform the continuous improvement program of increasing the community empowerment so that the rural communities may have good quality to be able to compete with other labors.
Jonker, J.B.; Meijaard, J.P.
2013-01-01
A beam finite element formulation for large deflection problems in the analysis of flexible multibody systems has been proposed. In this formulation, a set of independent discrete deformation modes are defined for each element which are related to conventional small deflection beam theory in a co-ro
Neural network for solving convex quadratic bilevel programming problems.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie
2014-03-01
In this paper, using the idea of successive approximation, we propose a neural network to solve convex quadratic bilevel programming problems (CQBPPs), which is modeled by a nonautonomous differential inclusion. Different from the existing neural network for CQBPP, the model has the least number of state variables and simple structure. Based on the theory of nonsmooth analysis, differential inclusions and Lyapunov-like method, the limit equilibrium points sequence of the proposed neural networks can approximately converge to an optimal solution of CQBPP under certain conditions. Finally, simulation results on two numerical examples and the portfolio selection problem show the effectiveness and performance of the proposed neural network.
A new algorithm for solving linear programming problems
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Andrés Leonardo Ramírez Leal
2012-08-01
Full Text Available Linear programming (LP is one of the most widely-applied techniques in operations research. Many methods have been developed and several others are being proposed for solving LP problems, including the famous simplex method and interior point algorithms. This study was aimed at introducing a new method for solving LP problems. The proposed algorithm starts from an interior point and then carries out orthogonal projections using parametric straight lines to move between the interior and polyhedron frontier defining the feasible region until reaching the extreme optimal point.
A convergence theory for a class of nonlinear programming problems.
Rauch, S. W.
1973-01-01
A recent convergence theory of Elkin concerning methods for unconstrained minimization is extended to a certain class of nonlinear programming problems. As in Elkin's original approach, the analysis of a variety of step-length algorithms is treated entirely separately from that of several direction algorithms. This allows for their combination into many different methods for solving the constrained problem. These include some of the methods of Rosen and Zoutendijk. We also extend the results of Topkis and Veinott to nonconvex sets and drop their requirement of the uniform feasibility of a subsequence of the search directions.
Optimality Conditions for Nondifferentiable Multiobjective Semi-Infinite Programming Problems
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D. Barilla
2016-01-01
Full Text Available We have considered a multiobjective semi-infinite programming problem with a feasible set defined by inequality constraints. First we studied a Fritz-John type necessary condition. Then, we introduced two constraint qualifications and derive the weak and strong Karush-Kuhn-Tucker (KKT in brief types necessary conditions for an efficient solution of the considered problem. Finally an extension of a Caristi-Ferrara-Stefanescu result for the (Φ,ρ-invexity is proved, and some sufficient conditions are presented under this weak assumption. All results are given in terms of Clark subdifferential.
Crasta, Graziano; Fragalà, Ilaria
2015-12-01
Given an open bounded subset Ω of {{R}^n}, which is convex and satisfies an interior sphere condition, we consider the pde {-Δ_{∞} u = 1} in Ω, subject to the homogeneous boundary condition u = 0 on ∂Ω. We prove that the unique solution to this Dirichlet problem is power-concave (precisely, 3/4 concave) and it is of class C 1( Ω). We then investigate the overdetermined Serrin-type problem, formerly considered in Buttazzo and Kawohl (Int Math Res Not, pp 237-247, 2011), obtained by adding the extra boundary condition {|nabla u| = a} on ∂Ω; by using a suitable P-function we prove that, if Ω satisfies the same assumptions as above and in addition contains a ball which touches ∂Ω at two diametral points, then the existence of a solution to this Serrin-type problem implies that necessarily the cut locus and the high ridge of Ω coincide. In turn, in dimension n = 2, this entails that Ω must be a stadium-like domain, and in particular it must be a ball in case its boundary is of class C 2.
New Integer Programming Formulations of the Generalized Travelling Salesman Problem
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P. C. Pop
2007-01-01
Full Text Available The Generalized Travelling Salesman Problem, denoted by GTSP, is a variant of the classical travelling salesman problem (TSP, in which the nodes of an undirected graph are partitioned into node sets (clusters and the salesman has to visit exactly one node from every cluster. In this paper we described six distinct formulations of the GTSP as an integer programming. Apart from the standard formulations all the new formulations that we describe are 'compact' in the sense that the number of constraints and variables is a polynomial function of the number of nodes in the problem. In order to provide compact formulations for the GTSP we used two approaches using auxiliary flow variables beyond the natural binary edge and node variables and the second one by distinguishing between global and local variables. Comparisons of the polytopes corresponding to their linear relaxations are established.
Motivating programming students by Problem Based Learning and LEGO robots
DEFF Research Database (Denmark)
Lykke, Marianne; Coto Chotto, Mayela; Mora, Sonia
2014-01-01
Retention of first year students in Computer Science is a concern for universities internationally. Especially programming courses are regarded as difficult, and often have the highest failure and dropout rates. The Informatics School at Universidad Nacional in Costa Rica is not an exception....... For this reason the school is focusing on different teaching methods to help their students master these skills. This paper introduces an experimental, controlled comparison study of three learning designs, involving a problem based learning (PBL) approach in connection with the use of LEGO Mindstorms to improve...... students programming skills and motivation for learning in an introductory programming course. The paper reports the results related with one of the components of the study - the experiential qualities of the three learning designs. The data were collected through a questionnaire survey with 229 students...
Maiti, Sumit Kumar; Roy, Sankar Kumar
2016-05-01
In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general transformation technique with the help of binary variables is used to transform the multi-choice type cost coefficients of the objective functions of Decision Makers(DMs). Then the transformed problem is considered as a deterministic multi-choice bi-level programming problem. Finally, a numerical example is presented to illustrate the usefulness of the paper.
A Constraint Programming Approach for Solving a Queueing Control Problem
Terekhov, Daria; 10.1613/jair.2446
2011-01-01
In a facility with front room and back room operations, it is useful to switch workers between the rooms in order to cope with changing customer demand. Assuming stochastic customer arrival and service times, we seek a policy for switching workers such that the expected customer waiting time is minimized while the expected back room staffing is sufficient to perform all work. Three novel constraint programming models and several shaving procedures for these models are presented. Experimental results show that a model based on closed-form expressions together with a combination of shaving procedures is the most efficient. This model is able to find and prove optimal solutions for many problem instances within a reasonable run-time. Previously, the only available approach was a heuristic algorithm. Furthermore, a hybrid method combining the heuristic and the best constraint programming method is shown to perform as well as the heuristic in terms of solution quality over time, while achieving the same performanc...
A Computer Program for a Canonical Problem in Underwater Shock
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Thomas L. Geers
1994-01-01
Full Text Available Finite-element/boundary-element codes are widely used to analyze the response of marine structures to underwater explosions. An important step in verifying the correctness and accuracy of such codes is the comparison of code-generated results for canonical problems with corresponding analytical or semianalytical results. At the present time, such comparisons rely on hardcopy results presented in technical journals and reports. This article describes a computer program available from SAVIAC that produces user-selected numerical results for a step-wave-excited spherical shell submerged in and (optionally filled with an acoustic fluid. The method of solution employed in the program is based on classical expansion of the field quantities in generalized Fourier series in the meridional coordinate. Convergence of the series is enhanced by judicious application of modified Cesàro summation and partial closed-form solution.
A recurrent neural network for solving bilevel linear programming problem.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian
2014-04-01
In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.
Integer programming for the generalized high school timetabling problem
DEFF Research Database (Denmark)
Kristiansen, Simon; Sørensen, Matias; Stidsen, Thomas Riis
2015-01-01
Recently, the XHSTT format for high school timetabling was introduced. It provides a uniform way of modeling problem instances and corresponding solutions. The format supports a wide variety of constraints, and currently 38 real-life instances from 11 different countries are available. Thereby......, the XHSTT format serves as a common ground for researchers within this area. This paper describes the first exact method capable of handling an arbitrary instance of the XHSTT format. The method is based on a mixed-integer linear programming (MIP) model, which is solved in two steps with a commercial...
Progressive geometric algorithms
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Sander P.A. Alewijnse
2015-01-01
Full Text Available Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms for two geometric problems: computing the convex hull of a planar point set, and finding popular places in a set of trajectories.
An optimization approach for the satisfiability problem
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S. Noureddine
2015-01-01
Full Text Available We describe a new approach for solving the satisfiability problem by geometric programming. We focus on the theoretical background and give details of the algorithmic procedure. The algorithm is provably efficient as geometric programming is in essence a polynomial problem. The correctness of the algorithm is discussed. The version of the satisfiability problem we study is exact satisfiability with only positive variables, which is known to be NP-complete.
Kassa, Semu Mitiku; Tsegay, Teklay Hailay
2017-08-01
Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.
Chisolm, Eric
2012-01-01
This is an introduction to geometric algebra, an alternative to traditional vector algebra that expands on it in two ways: 1. In addition to scalars and vectors, it defines new objects representing subspaces of any dimension. 2. It defines a product that's strongly motivated by geometry and can be taken between any two objects. For example, the product of two vectors taken in a certain way represents their common plane. This system was invented by William Clifford and is more commonly known as Clifford algebra. It's actually older than the vector algebra that we use today (due to Gibbs) and includes it as a subset. Over the years, various parts of Clifford algebra have been reinvented independently by many people who found they needed it, often not realizing that all those parts belonged in one system. This suggests that Clifford had the right idea, and that geometric algebra, not the reduced version we use today, deserves to be the standard "vector algebra." My goal in these notes is to describe geometric al...
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Päivi KINNUNEN
2005-10-01
Full Text Available We have applied Problem-Based Learning (PBL on an introductory programming course for several years with positive results. In this paper we present the outcomes and discuss our experiences of applying a modified version of PBL such that needs less tutoring resources and could better be used in large-scale courses, too. PBL has many positive effects on studying: Students report that they liked the social aspect of studying in a group. Generally students appreciated the possibility to be active participants in a course. On the other hand, group dynamic difficulties, tolerance of uncertainty and demanding studying skills caused problems that were too hard to overcome to some students. In this paper we introduce different versions of PBL, discuss efficiently and inefficiently working PBL groups and present their characters. We also discuss the possible reasons for differently working groups. Finally, we give some suggestions for interventions that might help the PBL groups to work better.
QUADRATIC BI-LEVEL PROGRAMMING PROBLEM BASED ON FUZZY GOAL PROGRAMMING APPROACH
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Partha Pratim Dey
2011-11-01
Full Text Available This paper presents fuzzy goal programming approach to quadratic bi-level programming problem. Inthe model formulation of the problem, we construct the quadratic membership functions by determiningindividual best solutions of the quadratic objective functions subject to the system constraints. Thequadratic membership functions are then transformed into equivalent linear membership functions byfirst order Taylor series approximation at the individual best solution point. Since the objectives of upperand lower level decision makers are potentially conflicting in nature, a possible relaxation of each leveldecisions are considered by providing preference bounds on the decision variables for avoiding decisiondeadlock. Then fuzzy goal programming approach is used for achieving highest degree of each of themembership goals by minimizing deviational variables. Numerical examples are provided in order todemonstrate the efficiency of the proposed approach.
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of so...
Problem Solving with an Icon Oriented Programming Tool: A Case Study in Technology Education.
Lavonen, Jari M.; Lattu, Matti; Meisalo, Veijo P.
2001-01-01
Finnish eighth graders used computer control software to find creative solutions to technological problems. The learning environment encouraged problem-centered and creative approaches. More systematic teaching of programming skills before problem solving was recommended. (Contains 32 references.) (SK)
Geometric inequalities methods of proving
Sedrakyan, Hayk
2017-01-01
This unique collection of new and classical problems provides full coverage of geometric inequalities. Many of the 1,000 exercises are presented with detailed author-prepared-solutions, developing creativity and an arsenal of new approaches for solving mathematical problems. This book can serve teachers, high-school students, and mathematical competitors. It may also be used as supplemental reading, providing readers with new and classical methods for proving geometric inequalities. .
Pebbling and Branching Programs Solving the Tree Evaluation Problem
Wehr, Dustin
2010-01-01
We study restricted computation models related to the Tree Evaluation Problem}. The TEP was introduced in earlier work as a simple candidate for the (*very*) long term goal of separating L and LogDCFL. The input to the problem is a rooted, balanced binary tree of height h, whose internal nodes are labeled with binary functions on [k] = {1,...,k} (each given simply as a list of k^2 elements of [k]), and whose leaves are labeled with elements of [k]. Each node obtains a value in [k] equal to its binary function applied to the values of its children, and the output is the value of the root. The first restricted computation model, called Fractional Pebbling, is a generalization of the black/white pebbling game on graphs, and arises in a natural way from the search for good upper bounds on the size of nondeterministic branching programs (BPs) solving the TEP - for any fixed h, if the binary tree of height h has fractional pebbling cost at most p, then there are nondeterministic BPs of size O(k^p) solving the heigh...
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Renata Melo e Silva de Oliveira
2015-03-01
Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests. With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs. The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
Geometric Computing for Freeform Architecture
Wallner, J.
2011-06-03
Geometric computing has recently found a new field of applications, namely the various geometric problems which lie at the heart of rationalization and construction-aware design processes of freeform architecture. We report on our work in this area, dealing with meshes with planar faces and meshes which allow multilayer constructions (which is related to discrete surfaces and their curvatures), triangles meshes with circle-packing properties (which is related to conformal uniformization), and with the paneling problem. We emphasize the combination of numerical optimization and geometric knowledge.
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Akimov Pavel Alekseevich
2012-10-01
Full Text Available The proposed paper covers the operator-related formulation of the eigenvalue problem of analysis of a three-dimensional structure that has piecewise-constant physical and geometrical parameters alongside the so-called basic direction within the framework of a discrete-continual approach (a discrete-continual finite element method, a discrete-continual variation method. Generally, discrete-continual formulations represent contemporary mathematical models that become available for computer implementation. They make it possible for a researcher to consider the boundary effects whenever particular components of the solution represent rapidly varying functions. Another feature of discrete-continual methods is the absence of any limitations imposed on lengths of structures. The three-dimensional problem of elasticity is used as the design model of a structure. In accordance with the so-called method of extended domain, the domain in question is embordered by an extended one of an arbitrary shape. At the stage of numerical implementation, relative key features of discrete-continual methods include convenient mathematical formulas, effective computational patterns and algorithms, simple data processing, etc. The authors present their formulation of the problem in question for an isotropic medium with allowance for supports restrained by elastic elements while standard boundary conditions are also taken into consideration.
Testing algebraic geometric codes
Institute of Scientific and Technical Information of China (English)
CHEN Hao
2009-01-01
Property testing was initially studied from various motivations in 1990's.A code C (∩)GF(r)n is locally testable if there is a randomized algorithm which can distinguish with high possibility the codewords from a vector essentially far from the code by only accessing a very small (typically constant) number of the vector's coordinates.The problem of testing codes was firstly studied by Blum,Luby and Rubinfeld and closely related to probabilistically checkable proofs (PCPs).How to characterize locally testable codes is a complex and challenge problem.The local tests have been studied for Reed-Solomon (RS),Reed-Muller (RM),cyclic,dual of BCH and the trace subcode of algebraicgeometric codes.In this paper we give testers for algebraic geometric codes with linear parameters (as functions of dimensions).We also give a moderate condition under which the family of algebraic geometric codes cannot be locally testable.
Testing algebraic geometric codes
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Property testing was initially studied from various motivations in 1990’s. A code C GF (r)n is locally testable if there is a randomized algorithm which can distinguish with high possibility the codewords from a vector essentially far from the code by only accessing a very small (typically constant) number of the vector’s coordinates. The problem of testing codes was firstly studied by Blum, Luby and Rubinfeld and closely related to probabilistically checkable proofs (PCPs). How to characterize locally testable codes is a complex and challenge problem. The local tests have been studied for Reed-Solomon (RS), Reed-Muller (RM), cyclic, dual of BCH and the trace subcode of algebraicgeometric codes. In this paper we give testers for algebraic geometric codes with linear parameters (as functions of dimensions). We also give a moderate condition under which the family of algebraic geometric codes cannot be locally testable.
Geometric interpretation of phyllotaxis transition
Okabe, Takuya
2012-01-01
The original problem of phyllotaxis was focused on the regular arrangements of leaves on mature stems represented by common fractions such as 1/2, 1/3, 2/5, 3/8, 5/13, etc. The phyllotaxis fraction is not fixed for each plant but it may undergo stepwise transitions during ontogeny, despite contrasting observation that the arrangement of leaf primordia at shoot apical meristems changes continuously. No explanation has been given so far for the mechanism of the phyllotaxis transition, excepting suggestion resorting to genetic programs operating at some specific stages. Here it is pointed out that varying length of the leaf trace acts as an important factor to control the transition by analyzing Larson's diagram of the procambial system of young cottonwood plants. The transition is interpreted as a necessary consequence of geometric constraints that the leaf traces cannot be fitted into a fractional pattern unless their length is shorter than the denominator times the internode.
Variance optimal stopping for geometric Levy processes
DEFF Research Database (Denmark)
Gad, Kamille Sofie Tågholt; Pedersen, Jesper Lund
2015-01-01
The main result of this paper is the solution to the optimal stopping problem of maximizing the variance of a geometric Lévy process. We call this problem the variance problem. We show that, for some geometric Lévy processes, we achieve higher variances by allowing randomized stopping. Furthermore...
Teaching Introductory Programming to IS Students: Java Problems and Pitfalls
Pendergast, Mark O.
2006-01-01
This paper examines the impact the use of the Java programming language has had on the way our students learn to program and the success they achieve. The importance of a properly constructed first course in programming cannot be overstated. A course well experienced will leave students with good programming habits, the ability to learn on their…
Teaching Introductory Programming to IS Students: Java Problems and Pitfalls
Pendergast, Mark O.
2006-01-01
This paper examines the impact the use of the Java programming language has had on the way our students learn to program and the success they achieve. The importance of a properly constructed first course in programming cannot be overstated. A course well experienced will leave students with good programming habits, the ability to learn on their…
Ambrosetti, Antonio; Malchiodi, Andrea
2009-01-01
This volume contains lecture notes on some topics in geometric analysis, a growing mathematical subject which uses analytical techniques, mostly of partial differential equations, to treat problems in differential geometry and mathematical physics. The presentation of the material should be rather accessible to non-experts in the field, since the presentation is didactic in nature. The reader will be provided with a survey containing some of the most exciting topics in the field, with a series of techniques used to treat such problems.
Nonconvex Quadratic Programming Method for κ-Coloring Problem: Algorithm and Computation
Institute of Scientific and Technical Information of China (English)
Cao Jiaming
1994-01-01
In this paper, we consider the socalled k-coloring problem in general case.Firstly, a special quadratic 0-1 programming is constructed to formulate k-coloring problem. Secondly, by use of the equivalence between above quadratic 0-1 programming and its relaxed rpoblem, k-coloring problem is converted into a class of (continuous) nonconvex quadratic programs, and several theoretic results are also introduced. Thirdly, linear programming approximate algorithm is quoted and verified for this class of nonconvex quadratic programs. Finally,examining problems which are used to test the algorithm are constructed and sufficient computation experiments are reported.
A Novel Tabular Form of the Simplex Method for Solving Linear Programming Problems
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Akaninyene Obot
2016-01-01
Full Text Available A new tabular form of the simplex method for solving linear programming problems is presented in this paper. There are many variants of the simplex method. The existing different tabular forms of the simplex method are difficult to comprehend, boring, not straight forward, confusing and tedious. The results obtained based on the proposed method are simpler and computationally more efficient for calculations of linear programs, than other competing simplex methods by other writers. The proposed method could be applied to solve Operations Research based problems in fuzzy linear programming, goal programming, transportation and assignment problems, game problems, and for carrying out sensitivity analysis in linear programming.
Finding Trustworthy Experts to Help Problem Solving on the Programming Learning Forum
Tseng, Shian-Shyong; Weng, Jui-Feng
2010-01-01
The most important thing for learners in Programming Language subject is problem solving. During the practical programming project, various problems may occur and learners usually need consultation from the senior programmers (i.e. the experts) to assist them in solving the problems. Thus, the inquiry-based learning with learning forum is applied…
COYOTE: a finite-element computer program for nonlinear heat-conduction problems
Energy Technology Data Exchange (ETDEWEB)
Gartling, D.K.
1982-10-01
COYOTE is a finite element computer program designed for the solution of two-dimensional, nonlinear heat conduction problems. The theoretical and mathematical basis used to develop the code is described. Program capabilities and complete user instructions are presented. Several example problems are described in detail to demonstrate the use of the program.
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Ebrahim Youness
1993-11-01
Full Text Available The problem dual to a multi-objective fractional programming problems is defined by using the concept of dual space of the objective space and using the concept of subgradient. Some assumptions considered in recent works are relaxed in our proposed approach.
Integrating packing and distribution problems and optimization through mathematical programming
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Fabio Miguel
2016-06-01
Full Text Available This paper analyzes the integration of two combinatorial problems that frequently arise in production and distribution systems. One is the Bin Packing Problem (BPP problem, which involves finding an ordering of some objects of different volumes to be packed into the minimal number of containers of the same or different size. An optimal solution to this NP-Hard problem can be approximated by means of meta-heuristic methods. On the other hand, we consider the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW, which is a variant of the Travelling Salesman Problem (again a NP-Hard problem with extra constraints. Here we model those two problems in a single framework and use an evolutionary meta-heuristics to solve them jointly. Furthermore, we use data from a real world company as a test-bed for the method introduced here.
Zörnig, Peter
2015-08-01
We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.
A bilinear programming solution to the quadratic assignment problem
J.F. Kaashoek (Johan); J.H.P. Paelinck (Jean)
1999-01-01
textabstractThe quadratic assignment problem (QAP) or maximum acyclical graph problem is well documented (see e.g. Pardalos and Wolkowicz, 1994). One of the authors has published some material, in which it was tried, by structuring the problem additionally, to bring it as closely as possible in the
Another Approach to Multiobjective Programming Problems with V-invex Functions
Institute of Scientific and Technical Information of China (English)
LIUSan-ming; FENGEn-min; LIXiao-shen
2005-01-01
In this paper, optimality conditions for multiobjective programming problems having V-invex objective and constraint functions are considered. An equivalent multiobjective programming problem is constructed by a modification of the objective function.Furthermore, a (α, η)-Lagrange function is introduced for a constructed multiobjective programming problem, and a new type of saddle point is introduced. Some results for the new type of saddle point are given.
de Klerk, E.; Sotirov, R.
2007-01-01
We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard,
Global Optimization of a Class of Nonconvex Quadratically Constrained Quadratic Programming Problems
Institute of Scientific and Technical Information of China (English)
Yong XIA
2011-01-01
In this paper we study a class of nonconvex quadratically constrained quadratic programming problems generalized from relaxations of quadratic assignment problems.We show that each problem is polynomially solved.Strong duality holds if a redundant constraint is introduced.As an application,a new lower bound is proposed for the quadratic assignment problem.
de Klerk, E.; Sotirov, R.
2007-01-01
We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard, S.
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
P. Bouman (Paul); N.A.H. Agatz (Niels); M.E. Schmidt (Marie)
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper
Global optimization over linear constraint non-convex programming problem
Institute of Scientific and Technical Information of China (English)
ZHANG Gui-Jun; WU Ti-Huan; YE Rong; YANG Hai-qing
2005-01-01
A improving Steady State Genetic Algorithm for global optimization over linear constraint non-convex programmin g problem is presented. By convex analyzing, the primal optimal problem can be converted to an equivalent problem, in which only the information of convex extremes of feasible space is included, and is more easy for GAs to solve. For avoiding invalid genetic operators, a redesigned convex crossover operator is also performed in evolving. As a integrality, the quality of two problem is proven, and a method is also given to get all extremes in linear constraint space. Simulation result show that new algorithm not only converges faster, but also can maintain an diversity population, and can get the global optimum of test problem.
Special Concretes and Field Problems; Instructor's Guide; Pilot Program Edition.
Portland Cement Association, Cleveland, OH.
This guide, prepared for a 2-year program in junior colleges and technical institutes, is designed for a national program to train persons for employment as technicians in the cement and concrete industries. Included are 48 session oultines divided into four units of study. Each unit contains session objectives and outlines, presentation outlines,…
UNITE and Management Training Program for Workplace Communication & Problem Solving.
Kaufman, Sanda
This curriculum provides materials for a training program designed to enable front-line supervisors and union stewards to minimize production disruptions stemming from ongoing, unresolved conflicts among production workers. The program accomplishes this goal by giving participants the tools and confidence to design, implement, and run a process…
Dijkstra's interpretation of the approach to solving a problem of program correctness
Directory of Open Access Journals (Sweden)
Markoski Branko
2010-01-01
Full Text Available Proving the program correctness and designing the correct programs are two connected theoretical problems, which are of great practical importance. The first is solved within program analysis, and the second one in program synthesis, although intertwining of these two processes is often due to connection between the analysis and synthesis of programs. Nevertheless, having in mind the automated methods of proving correctness and methods of automatic program synthesis, the difference is easy to tell. This paper presents denotative interpretation of programming calculation explaining semantics by formulae φ and ψ, in such a way that they can be used for defining state sets for program P.
Multi-objective convex programming problem arising in multivariate ...
African Journals Online (AJOL)
user
International Journal of Engineering, Science and Technology. Vol. ... However, although the consideration of multiple objectives may seem a novel concept, virtually any nontrivial, real world problem invariably involves multiple objectives.
de Klerk, E.; Sotirov, R.; Truetsch, U.
2015-01-01
Recent progress in solving quadratic assignment problems (QAPs) from the QAPLIB (Quadratic Assignment Problem Library) test set has come from mixed-integer linear or quadratic programming models that are solved in a branch-and-bound framework. Semidefinite programming (SDP) bounds for QAPs have also
Developing Student Programming and Problem-Solving Skills with Visual Basic
Siegle, Del
2009-01-01
Although most computer users will never need to write a computer program, many students enjoy the challenge of creating one. Computer programming enhances students' problem solving by forcing students to break a problem into its component pieces and reassemble it in a generic format that can be understood by a nonsentient entity. It promotes…
A Rapid Grid Search Method for Solving Dynamic Programming Problems in Economics
Hui He; Hao Zhang
2013-01-01
We introduce a rapid grid search method in solving dynamic programming problems in economics. Compared to mainstream grid search methods, by using local information of the Bellman equation, this method can significantly increase the efficiency in solving dynamic programming problems by reducing the grid points searched in the control space.
A Note on a Rapid Grid Search Method for Solving Dynamic Programming Problems in Economics
Hui He; Hao Zhang
2010-01-01
We introduce a rapid grid search method in solving the dynamic programming problems in economics. Compared to mainstream grid search methods, by using local information of the Bellman equation, this method can significantly increase the efficiency in solving dynamic programming problems by reducing the grid points searched in the control space.
Solving fully fuzzy multiple objective linear programming problems: A new perspective
A. Hadi-Vencheh; Z Rezaei; S. Razipour
2014-01-01
In this paper a systematic process has been proposed to solve a fully fuzzy multi objective linear programming problem (FFMOLPP). Using the utility vector the MOLPP is transferred to a single objective programming and this single fuzzy object problem is simply solved by one of the fuzzy approaches.A numerical example is then given to show applicability of the proposed approach.
Stacked Deck: An Effective, School-Based Program for the Prevention of Problem Gambling
Williams, Robert J.; Wood, Robert T.; Currie, Shawn R.
2010-01-01
School-based prevention programs are an important component of problem gambling prevention, but empirically effective programs are lacking. Stacked Deck is a set of 5-6 interactive lessons that teach about the history of gambling; the true odds and "house edge"; gambling fallacies; signs, risk factors, and causes of problem gambling; and…
Creating a Brighter Future: An Update on the Future Problem Solving Program.
Crabbe, Anne Borland
1982-01-01
The Future Problem Solving Program is intended to help gifted students (grades 4 through 12) develop richer images of the future and increase creativity, communication, teamwork, research, and problem-solving skills. Procedures for participating in the program and securing materials are explained. (CL)
An Integer Programming-based Local Search for Large-scale Maximal Covering Problems
Directory of Open Access Journals (Sweden)
Junha Hwang
2011-02-01
Full Text Available Maximal covering problem (MCP is classified as a linear integer optimization problem which can be effectively solved by integer programming technique. However, as the problem size grows, integerprogramming requires excessive time to get an optimal solution. This paper suggests a method for applying integer programming-based local search (IPbLS to solve large-scale maximal covering problems. IPbLS, which is a hybrid technique combining integer programming and local search, is a kind of local search using integer programming for neighbor generation. IPbLS itself is very effective for MCP. In addition, we improve the performance of IPbLS for MCP through problem reduction based on the current solution. Experimental results show that the proposed method considerably outperforms any other local search techniques and integer programming.
A MATHEMATICAL PROGRAMMING MODEL FOR THE COEXISTENCE OF COMPETITIONS AND COOPERATIONS PROBLEMS
Institute of Scientific and Technical Information of China (English)
MENG Zhiqing; HU Qiying; DANG Changyan
2005-01-01
We study in. This paper a mathematical programming model for the coexistence of competitions and cooperations problems. We introduce a new solution concept,s-optimal solution for the problem, which always exists under compact and continuous conditions. It is shown that an s-optimal solution can be obtained by solving a nonlinear programming problem. Some examples are given to explain how to compute an s-optimal solution.
Institute of Scientific and Technical Information of China (English)
陈志平
2003-01-01
A new deterministic formulation,called the conditional expectation formulation,is proposed for dynamic stochastic programming problems in order to overcome some disadvantages of existing deterministic formulations.We then check the impact of the new deterministic formulation and other two deterministic formulations on the corresponding problem size,nonzero elements and solution time by solving some typical dynamic stochastic programming problems with different interior point algorithms.Numerical results show the advantage and application of the new deterministic formulation.
Zu-Tong Wang; Jian-Sheng Guo; Ming-Fa Zheng; Ying Wang
2014-01-01
Based on the credibility theory, this paper is devoted to the fuzzy multiobjective programming problem. Firstly, the expected-value model of fuzzy multiobjective programming problem is provided based on credibility theory; then two new approaches for obtaining efficient solutions are proposed on the basis of the expected-value model, whose validity has been proven. For solving the fuzzy MOP problem efficiently, Latin hypercube sampling, fuzzy simulation, support vector machine, an...
Method for solving fully fuzzy linear programming problems using deviation degree measure
Institute of Scientific and Technical Information of China (English)
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
A new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique.
A smoothing Newton method for a type of inverse semi-definite quadratic programming problem
Xiao, Xiantao; Zhang, Liwei; Zhang, Jianzhong
2009-01-01
We consider an inverse problem arising from the semi-definite quadratic programming (SDQP) problem. We represent this problem as a cone-constrained minimization problem and its dual (denoted ISDQD) is a semismoothly differentiable (SC1) convex programming problem with fewer variables than the original one. The Karush-Kuhn-Tucker conditions of the dual problem (ISDQD) can be formulated as a system of semismooth equations which involves the projection onto the cone of positive semi-definite matrices. A smoothing Newton method is given for getting a Karush-Kuhn-Tucker point of ISDQD. The proposed method needs to compute the directional derivative of the smoothing projector at the corresponding point and to solve one linear system per iteration. The quadratic convergence of the smoothing Newton method is proved under a suitable condition. Numerical experiments are reported to show that the smoothing Newton method is very effective for solving this type of inverse quadratic programming problems.
Nakata, M.; Muramatsu, M.; Waki, H.
2008-01-01
We observe that in a simple one-dimensional polynomial optimization problem (POP), the `optimal' values of semidefinite programming (SDP) relaxation problems reported by the standard SDP solvers converge to the optimal value of the POP, while the true optimal values of SDP relaxation problems are st
How Does Early Feedback in an Online Programming Course Change Problem Solving?
Ebrahimi, Alireza
2012-01-01
How does early feedback change the programming problem solving in an online environment and help students choose correct approaches? This study was conducted in a sample of students learning programming in an online course entitled Introduction to C++ and OOP (Object Oriented Programming) using the ANGEL learning management system platform. My…
Integer programming for the generalized high school timetabling problem
DEFF Research Database (Denmark)
Kristiansen, Simon; Sørensen, Matias; Stidsen, Thomas Riis
2015-01-01
Recently, the XHSTT format for high school timetabling was introduced. It provides a uniform way of modeling problem instances and corresponding solutions. The format supports a wide variety of constraints, and currently 38 real-life instances from 11 different countries are available. Thereby...
Optimal Geometric Partitions, Covers and K-Centers
Andreica, Mugurel Ionut; Andreica, Cristina Teodora; Andreica, Romulus; Ungureanu, Mihai Aristotel
2009-01-01
In this paper we present some new, practical, geometric optimization techniques for computing polygon partitions, 1D and 2D point, interval, square and rectangle covers, as well as 1D and 2D interval and rectangle K-centers. All the techniques we present have immediate applications to several cost optimization and facility location problems which are quite common in practice. The main technique employed is dynamic programming, but we also make use of efficient data structures and fast greedy algorithms.
Documentation as Problem Solving for Literacy Outreach Programs
Energy Technology Data Exchange (ETDEWEB)
Girill, T R
2004-07-06
Age-appropriate technical writing lessons for underperforming high-school students can offer them an innovative, ''authentic'' way to improve how they read and write. Thus the techniques and principles of effective technical communication routinely applied at work also provide a positive response to one of today's great educational challenges. This workshop shows participants how to (1) introduce English and science teachers to the value of technical writing as a response to school literacy problems, (2) prepare plausible practice exercises to help students improve their basic literacy, and (3) recognize and respond to known literacy outreach pitfalls. Every effective literacy outreach project based on technical writing needs to address four key problems.
Directory of Open Access Journals (Sweden)
Weihua Jin
2013-01-01
Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.
An introduction to fuzzy linear programming problems theory, methods and applications
Kaur, Jagdeep
2016-01-01
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Solving Segment Routing Problems with Hybrid Constraint Programming Techniques
Hartert, Renaud; Schaus, Pierre; Vissicchio, Stefano; Bonaventure, Olivier; International Conference on Principles and Practice of Constraint Programming (CP2014)
2015-01-01
Segment routing is an emerging network technology that exploits the existence of several paths between a source and a destination to spread the traffic in a simple and elegant way. The major commercial network vendors already support segment routing, and several Internet actors are ready to use segment routing in their network. Unfortunately, by changing the way paths are computed, segment routing poses new op- timization problems which cannot be addressed with previous research contributions...
Directory of Open Access Journals (Sweden)
S.K. Barik
2015-06-01
Full Text Available In many real-life decision making problems, probabilistic fuzzy goal programming problems are used where some of the input parameters of the problem are considered as random variables with fuzzy aspiration levels. In the present paper, a linearly constrained probabilistic fuzzy goal programming programming problem is presented where the right hand side parameters in some constraints follows Pareto distribution with known mean and variance. Also the aspiration levels are considered as fuzzy. Further, simple, weighted, and preemptive additive approaches are discussed for probabilistic fuzzy goal programming model. These additive approaches are employed to aggregating the membership values and form crisp equivalent deterministic models. The resulting models are then solved by using standard linear mathematical programming techniques. The developed methodology and solution procedures are illustrated with a numerical example.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Institute of Scientific and Technical Information of China (English)
G.J. Zalmai; Qing-hong Zhang
2007-01-01
A semi-infinite programming problem is a mathematical programming problem with a finite number of variables and infinitely many constraints. Duality theories and generalized convexity concepts are important research topics in mathematical programming. In this paper, we discuss a fairly large number of parametric duality results under various generalized (η, p)-invexity assumptions for a semi-infinite minmax fractional programming problem.
Directory of Open Access Journals (Sweden)
Mansour Saraj
2012-06-01
Full Text Available In this paper we propose a fuzzy goal programming method for obtaining a satisfactory solution to a bi-level multi-objective absolute-value fractional programming (BLMO-A-FP problems. In the proposed approach, the membership functions for the de ned fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by upper level decision maker (ULDM are developed in the model formulation of the problem. Then fuzzy goal programming technique is used for achieving highest degree of each of the membership goals by minimizing negative and positive deviational variables. The method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem eciently by using linear goal programming methodology. Theoretical results is illustrated with the help of a numerical.
Guide to Geometric Algebra in Practice
Dorst, Leo
2011-01-01
This highly practical "Guide to Geometric Algebra in Practice" reviews algebraic techniques for geometrical problems in computer science and engineering, and the relationships between them. The topics covered range from powerful new theoretical developments, to successful applications, and the development of new software and hardware tools. This title: provides hands-on review exercises throughout the book, together with helpful chapter summaries; presents a concise introductory tutorial to conformal geometric algebra (CGA) in the appendices; examines the application of CGA for the d
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
of the maximum lifetime routing problem that considers the operation modes of the node. Solution of the linear programming gives the upper analytical bound for the network lifetime. In order to illustrate teh application of the optimization model, we solved teh problem for different parameter settings...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
Energy Technology Data Exchange (ETDEWEB)
Wos, L.; McCune, W.
1988-01-01
In this paper, we offer a set of problems for evaluating the power of automated theorem-proving programs and the potential of new ideas. Since the problems published in the proceedings of the first CADE conference proved to be so useful, and since researchers are now far more disposed to implementing and testing their ideas, a new set of problems to complement those that have been widely studied is in order. In general, the new problems provide a far greater challenge for an automated theorem-proving program than those in the first set do. Indeed, to our knowledge, five of the six problems we propose for study have never been proved with a theorem-proving program. For each problem, we give a set of statements that can easily be translated into a standard set of clauses. We also state each problem in its mathematical and logical form. In many cases, we also provide a proof of the theorem from which a problem is taken so that one can measure a program's progress in its attempt to solve the problem. Two of the theorems we discuss are of especial interest in that they answer questions that had been open concerning the constructibility of two types of combinator. We also include a brief description of a new strategy for restricting the application of paramodulation. All of the problems we propose for study emphasize the role of equality. This paper is tutorial in nature.
Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters
Directory of Open Access Journals (Sweden)
S. K. Barik
2012-01-01
making problem by using some specified random variables and fuzzy numbers. In the present paper, randomness is characterized by Weibull random variables and fuzziness is characterized by triangular and trapezoidal fuzzy number. A defuzzification method has been introduced for finding the crisp values of the fuzzy numbers using the proportional probability density function associated with the membership functions of these fuzzy numbers. An equivalent deterministic crisp model has been established in order to solve the proposed model. Finally, a numerical example is presented to illustrate the solution procedure.
Motivating programming students by Problem Based Learning and LEGO robots
DEFF Research Database (Denmark)
Lykke, Marianne; Coto Chotto, Mayela; Mora, Sonia
2014-01-01
. For this reason the school is focusing on different teaching methods to help their students master these skills. This paper introduces an experimental, controlled comparison study of three learning designs, involving a problem based learning (PBL) approach in connection with the use of LEGO Mindstorms to improve...... from three groups exposed to different learning designs and through six qualitative walk-alongs collecting data from these groups by informal interviews and observations. Findings from the three studies were discussed in three focus group interviews with 10 students from the three experimental groups....
Directory of Open Access Journals (Sweden)
Elena P. Rostova
2011-05-01
Full Text Available In the article is the problem of distribution of resources of the insurance company, as well as its mathematical record. The distribution of resources is carried out between the insurance services for a certain number of time intervals.
The general form of 0-1 programming problem based on DNA computing.
ZhiXiang, Yin; Fengyue, Zhang; Jin, Xu
2003-06-01
DNA computing is a novel method of solving a class of intractable computational problems, in which the computing speeds up exponentially with the problem size. Up to now, many accomplishments have been made to improve its performance and increase its reliability. In this paper, we solved the general form of 0-1 programming problem with fluorescence labeling techniques based on surface chemistry by attempting to apply DNA computing to a programming problem. Our method has some significant advantages such as simple encoding, low cost, and short operating time.
A Comparative Study of Redundant Constraints Identification Methods in Linear Programming Problems
Directory of Open Access Journals (Sweden)
Paulraj S.
2010-01-01
Full Text Available The objective function and the constraints can be formulated as linear functions of independent variables in most of the real-world optimization problems. Linear Programming (LP is the process of optimizing a linear function subject to a finite number of linear equality and inequality constraints. Solving linear programming problems efficiently has always been a fascinating pursuit for computer scientists and mathematicians. The computational complexity of any linear programming problem depends on the number of constraints and variables of the LP problem. Quite often large-scale LP problems may contain many constraints which are redundant or cause infeasibility on account of inefficient formulation or some errors in data input. The presence of redundant constraints does not alter the optimal solutions(s. Nevertheless, they may consume extra computational effort. Many researchers have proposed different approaches for identifying the redundant constraints in linear programming problems. This paper compares five of such methods and discusses the efficiency of each method by solving various size LP problems and netlib problems. The algorithms of each method are coded by using a computer programming language C. The computational results are presented and analyzed in this paper.
A Mathematical Programming Approach to the Fractionation Problem in Chemoradiotherapy
Salari, Ehsan; Bortfeld, Thomas
2013-01-01
In concurrent chemoradiotherapy, chemotherapeutic agents are administered during the course of radiotherapy to enhance the primary tumor control. However, that often comes at the expense of increased risk of normal-tissue complications. The additional biological damage is mainly attributed to two mechanisms of action, which are the independent cytotoxic activity of chemotherapeutic agents and their interactive cooperation with radiation. The goal of this study is to develop a mathematical framework to obtain drug and radiation administration schedules that maximize the therapeutic gain for concurrent chemoradiotherapy. In particular, we analyze the impact of incorporating these two mechanisms into the radiation fractionation problem. Considering each mechanism individually, we first derive closed-form expressions for the optimal radiation fractionation regimen and the corresponding drug administration schedule. We next study the case in which both mechanisms are simultaneously present and develop a dynamic pr...
Nonlinear programming for classification problems in machine learning
Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio
2016-10-01
We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.
Bidimensionality and Geometric Graphs
Fomin, Fedor V; Saurabh, Saket
2011-01-01
In this paper we use several of the key ideas from Bidimensionality to give a new generic approach to design EPTASs and subexponential time parameterized algorithms for problems on classes of graphs which are not minor closed, but instead exhibit a geometric structure. In particular we present EPTASs and subexponential time parameterized algorithms for Feedback Vertex Set, Vertex Cover, Connected Vertex Cover, Diamond Hitting Set, on map graphs and unit disk graphs, and for Cycle Packing and Minimum-Vertex Feedback Edge Set on unit disk graphs. Our results are based on the recent decomposition theorems proved by Fomin et al [SODA 2011], and our algorithms work directly on the input graph. Thus it is not necessary to compute the geometric representations of the input graph. To the best of our knowledge, these results are previously unknown, with the exception of the EPTAS and a subexponential time parameterized algorithm on unit disk graphs for Vertex Cover, which were obtained by Marx [ESA 2005] and Alber and...
Manwani, Naresh
2010-01-01
In this paper we present a new algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess the goodness of hyperplanes at each node while learning a decision tree in a top-down fashion. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy to assess the hyperplanes in such a way that the geometric structure in the data is taken into account. At each node of the decision tree, we find the clustering hyperplanes for both the classes and use their angle bisectors as the split rule at that node. We show through empirical studies that this idea leads to small decision trees and better performance. We also present some analysis to show that the angle bisectors of clustering hyperplanes that we use as the split rules at each node, are solutions of an interesting optimization problem and hence argue that this is a principled method of learning a decision tree.
BILEVEL PROGRAMMING MODEL AND SOLUTION METHOD FOR MIXED TRANSPORTATION NETWORK DESIGN PROBLEM
Institute of Scientific and Technical Information of China (English)
Haozhi ZHANG; Ziyou GAO
2009-01-01
By handling the travel cost function artfully, the authors formulate the transportation mixed network design problem (MNDP) as a mixed-integer, nonlinear bilevel programming problem, in which the lower-level problem, comparing with that of conventional bilevel DNDP models, is not a side constrained user equilibrium assignment problem, but a standard user equilibrium assignment problem. Then, the bilevel programming model for MNDP is reformulated as a continuous version of bilevel programming problem by the continuation method. By virtue of the optimal-value function, the lower-level assignment problem can be expressed as a nonlinear equality constraint. Therefore, the bilevel programming model for MNDP can be transformed into an equivalent single-level optimization problem. By exploring the inherent nature of the MNDP, the optimal-value function for the lower-level equilibrium assignment problem is proved to be continuously differentiable and its functional value and gradient can be obtained efficiently. Thus, a continuously differentiable but still nonconvex optimization formulation of the MNDP is created, and then a locally convergent algorithm is proposed by applying penalty function method. The inner loop of solving the subproblem is mainly to implement an all-or-nothing assignment. Finally, a small-scale transportation network and a large-scale network are presented to verify the proposed model and algorithm.
Sensitivity analysis of efficient solution in vector MINMAX boolean programming problem
Directory of Open Access Journals (Sweden)
Vladimir A. Emelichev
2002-11-01
Full Text Available We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal solution preserves optimality was obtained.
The Expansion of Dynamic Solving Process About a Class of Non-linear Programming Problems
Institute of Scientific and Technical Information of China (English)
ZANG Zhen-chun
2001-01-01
In this paper, we research non-linear programming problems which have a given specialstructure, some simple forms of this kind structure have been solved in some papers, here we focus on othercomplex ones.
A high-performance feedback neural network for solving convex nonlinear programming problems.
Leung, Yee; Chen, Kai-Zhou; Gao, Xing-Bao
2003-01-01
Based on a new idea of successive approximation, this paper proposes a high-performance feedback neural network model for solving convex nonlinear programming problems. Differing from existing neural network optimization models, no dual variables, penalty parameters, or Lagrange multipliers are involved in the proposed network. It has the least number of state variables and is very simple in structure. In particular, the proposed network has better asymptotic stability. For an arbitrarily given initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem under no more than the standard assumptions. In addition, the network can also solve linear programming and convex quadratic programming problems, and the new idea of a feedback network may be used to solve other optimization problems. Feasibility and efficiency are also substantiated by simulation examples.
A New Global Optimization Algorithm for Solving a Class of Nonconvex Programming Problems
Directory of Open Access Journals (Sweden)
Xue-Gang Zhou
2014-01-01
Full Text Available A new two-part parametric linearization technique is proposed globally to a class of nonconvex programming problems (NPP. Firstly, a two-part parametric linearization method is adopted to construct the underestimator of objective and constraint functions, by utilizing a transformation and a parametric linear upper bounding function (LUBF and a linear lower bounding function (LLBF of a natural logarithm function and an exponential function with e as the base, respectively. Then, a sequence of relaxation lower linear programming problems, which are embedded in a branch-and-bound algorithm, are derived in an initial nonconvex programming problem. The proposed algorithm is converged to global optimal solution by means of a subsequent solution to a series of linear programming problems. Finally, some examples are given to illustrate the feasibility of the presented algorithm.
Asymptotic geometric analysis, part I
Artstein-Avidan, Shiri
2015-01-01
The authors present the theory of asymptotic geometric analysis, a field which lies on the border between geometry and functional analysis. In this field, isometric problems that are typical for geometry in low dimensions are substituted by an "isomorphic" point of view, and an asymptotic approach (as dimension tends to infinity) is introduced. Geometry and analysis meet here in a non-trivial way. Basic examples of geometric inequalities in isomorphic form which are encountered in the book are the "isomorphic isoperimetric inequalities" which led to the discovery of the "concentration phenomen
A Framework for Analyzing Geometric Pattern Tasks
Friel, Susan N.; Markworth, Kimberly A.
2009-01-01
Teachers can use geometric patterns to promote students' understanding of functional relationships. In this article, the authors first look at a problem-solving process that supports the use of figural reasoning to explore and interpret geometric pattern tasks and generalize function rules. Second, the authors discuss a framework for…
Solution for integer linear bilevel programming problems using orthogonal genetic algorithm
Institute of Scientific and Technical Information of China (English)
Hong Li; Li Zhang; Yongchang Jiao
2014-01-01
An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit program-ming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the ortho-gonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as off-spring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algo-rithm.
Nasini, Stefano
2015-01-01
The thesis deals with the theoretical and practical study of mathematical programming methodologies to the analysis complex networks and their application in economic and social problems. More specifically, it applies models and methods for solving linear and integer programming problems to network models exploiting the matrix structure of such models, resulting in efficient computational procedures and small processing time. As a consequence, it allows the study of larger and more complex n...
GOAL PROGRAMMING ALGORITHM FOR A TYPE OF LEAST ABSOLUTE VALUE REGRESSION PROBLEM
Institute of Scientific and Technical Information of China (English)
SHI Kuiran; XIAO Tiaojun; ZHANG Weirong
2004-01-01
This paper develops goal programming algorithm to solve a type of least absolute value (LAV) problem. Firstly, we simplify the simplex algorithm by proving the existence of solutions of the problem. Then, we present a goal programming algorithm on the basis of the original techniques. Theoretical analysis and numerical results indicate that the new method contains a lower number of deviation variables and consumes less computational time as compared to current LAV methods.
Solving fully fuzzy multiple objective linear programming problems: A new perspective
Directory of Open Access Journals (Sweden)
A. Hadi-Vencheh
2014-08-01
Full Text Available In this paper a systematic process has been proposed to solve a fully fuzzy multi objective linear programming problem (FFMOLPP. Using the utility vector the MOLPP is transferred to a single objective programming and this single fuzzy object problem is simply solved by one of the fuzzy approaches.A numerical example is then given to show applicability of the proposed approach.
Optimality Condition and Wolfe Duality for Invex Interval-Valued Nonlinear Programming Problems
Directory of Open Access Journals (Sweden)
Jianke Zhang
2013-01-01
Full Text Available The concepts of preinvex and invex are extended to the interval-valued functions. Under the assumption of invexity, the Karush-Kuhn-Tucker optimality sufficient and necessary conditions for interval-valued nonlinear programming problems are derived. Based on the concepts of having no duality gap in weak and strong sense, the Wolfe duality theorems for the invex interval-valued nonlinear programming problems are proposed in this paper.
Geometric Modeling Application Interface Program
1990-11-01
Manual IDEF-Extended ( IDEFIX ) Integrated Information Support System (IISS), ICAM Project 6201, Contract F33615-80-C-5155, December 1985. Interim...Differential Geometry of Curves and Surfaces, M. P. de Carmo, Prentice-Hall, Inc., 1976. IDEFIX Readers Reference, D. Appleton Company, December 1985...Modeling. IDEFI -- IDEF Information Modeling. IDEFIX -- IDEF Extended Information Modeling. IDEF2 -- IDEF Dynamics Modeling. IDSS -- Integrated Decision
Geometric Approaches to Quadratic Equations from Other Times and Places.
Allaire, Patricia R.; Bradley, Robert E.
2001-01-01
Focuses on geometric solutions of quadratic problems. Presents a collection of geometric techniques from ancient Babylonia, classical Greece, medieval Arabia, and early modern Europe to enhance the quadratic equation portion of an algebra course. (KHR)
Tapia, R. A.; Vanrooy, D. L.
1976-01-01
A quasi-Newton method is presented for minimizing a nonlinear function while constraining the variables to be nonnegative and sum to one. The nonnegativity constraints were eliminated by working with the squares of the variables and the resulting problem was solved using Tapia's general theory of quasi-Newton methods for constrained optimization. A user's guide for a computer program implementing this algorithm is provided.
Federal Laboratory Consortium — Purpose: The mission of the Geometric Design Laboratory (GDL) is to support the Office of Safety Research and Development in research related to the geometric design...
On Geometric Infinite Divisibility
Sandhya, E.; Pillai, R. N.
2014-01-01
The notion of geometric version of an infinitely divisible law is introduced. Concepts parallel to attraction and partial attraction are developed and studied in the setup of geometric summing of random variables.
Higher-Dimensional Geometric $\\sigma$-Models
Vasilic, M
1999-01-01
Geometric $\\sigma$-models have been defined as purely geometric theories of scalar fields coupled to gravity. By construction, these theories possess arbitrarily chosen vacuum solutions. Using this fact, one can build a Kaluza--Klein geometric $\\sigma$-model by specifying the vacuum metric of the form $M^4\\times B^d$. The obtained higher dimensional theory has vanishing cosmological constant but fails to give massless gauge fields after the dimensional reduction. In this paper, a modified geometric $\\sigma$-model is suggested, which solves the above problem.
An Integer Programming Formulation of the Minimum Common String Partition Problem.
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S M Ferdous
Full Text Available We consider the problem of finding a minimum common string partition (MCSP of two strings, which is an NP-hard problem. The MCSP problem is closely related to genome comparison and rearrangement, an important field in Computational Biology. In this paper, we map the MCSP problem into a graph applying a prior technique and using this graph, we develop an Integer Linear Programming (ILP formulation for the problem. We implement the ILP formulation and compare the results with the state-of-the-art algorithms from the literature. The experimental results are found to be promising.
Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program
Akcaoglu, Mete
2014-01-01
Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
of the maximum lifetime routing problem that considers the operation modes of the node. Solution of the linear programming gives the upper analytical bound for the network lifetime. In order to illustrate teh application of the optimization model, we solved teh problem for different parameter settings...
Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program
Akcaoglu, Mete
2014-01-01
Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…
Adventure Camp Programs, Self-Concept, and Their Effects on Behavioral Problem Adolescents
Larson, Bruce A.
2007-01-01
The purpose of this study was to examine the effects of an adventure camp program on the self-concept of adolescents with behavioral problems. Subjects in the study included 61 randomly selected male and female adolescents ranging in age from 9 to 17 years with behavioral problems. The treatment group of 31 adolescents was randomly selected from a…
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
A Smooth Newton Method for Nonlinear Programming Problems with Inequality Constraints
Directory of Open Access Journals (Sweden)
Vasile Moraru
2012-02-01
Full Text Available The paper presents a reformulation of the Karush-Kuhn-Tucker (KKT system associated nonlinear programming problem into an equivalent system of smooth equations. Classical Newton method is applied to solve the system of equations. The superlinear convergence of the primal sequence, generated by proposed method, is proved. The preliminary numerical results with a problems test set are presented.
Analysis of Learning Behavior in a Flipped Programing Classroom Adopting Problem-Solving Strategies
Chiang, Tosti Hsu-Cheng
2017-01-01
Programing is difficult for beginners because they need to learn the new language of computers. Developing software, especially complex software, is bound to result in problems, frustration, and the need to think in new ways. Identifying the learning behavior behind programing by way of empirical studies can help beginners learn more easily. In…
Allinjawi, Arwa A.; Al-Nuaim, Hana A.; Krause, Paul
2014-01-01
Students often face difficulties while learning object-oriented programming (OOP) concepts. Many papers have presented various assessment methods for diagnosing learning problems to improve the teaching of programming in computer science (CS) higher education. The research presented in this article illustrates that although max-min composition is…
Geometric procedures for civil engineers
Tonias, Elias C
2016-01-01
This book provides a multitude of geometric constructions usually encountered in civil engineering and surveying practice. A detailed geometric solution is provided to each construction as well as a step-by-step set of programming instructions for incorporation into a computing system. The volume is comprised of 12 chapters and appendices that may be grouped in three major parts: the first is intended for those who love geometry for its own sake and its evolution through the ages, in general, and, more specifically, with the introduction of the computer. The second section addresses geometric features used in the book and provides support procedures used by the constructions presented. The remaining chapters and the appendices contain the various constructions. The volume is ideal for engineering practitioners in civil and construction engineering and allied areas.
Airborne Linear Array Image Geometric Rectification Method Based on Unequal Segmentation
Li, J. M.; Li, C. R.; Zhou, M.; Hu, J.; Yang, C. M.
2016-06-01
As the linear array sensor such as multispectral and hyperspectral sensor has great potential in disaster monitoring and geological survey, the quality of the image geometric rectification should be guaranteed. Different from the geometric rectification of airborne planar array images or multi linear array images, exterior orientation elements need to be determined for each scan line of single linear array images. Internal distortion persists after applying GPS/IMU data directly to geometrical rectification. Straight lines may be curving and jagged. Straight line feature -based geometrical rectification algorithm was applied to solve this problem, whereby the exterior orientation elements were fitted by piecewise polynomial and evaluated with the straight line feature as constraint. However, atmospheric turbulence during the flight is unstable, equal piecewise can hardly provide good fitting, resulting in limited precision improvement of geometric rectification or, in a worse case, the iteration cannot converge. To solve this problem, drawing on dynamic programming ideas, unequal segmentation of line feature-based geometric rectification method is developed. The angle elements fitting error is minimized to determine the optimum boundary. Then the exterior orientation elements of each segment are fitted and evaluated with the straight line feature as constraint. The result indicates that the algorithm is effective in improving the precision of geometric rectification.
A Mixed Integer Programming Model Formulation for Solving the Lot-Sizing Problem
Mohammadi, Maryam
2012-01-01
This paper addresses a mixed integer programming (MIP) formulation for the multi-item uncapacitated lot-sizing problem that is inspired from the trailer manufacturer. The proposed MIP model has been utilized to find out the optimum order quantity, optimum order time, and the minimum total cost of purchasing, ordering, and holding over the predefined planning horizon. This problem is known as NP-hard problem. The model was presented in an optimal software form using LINGO 13.0.
Parallel Programming Methodologies for Non-Uniform Structured Problems in Materials Science
1993-10-01
COVERED 1 10/93 _ Interim 12/01/92 - 09/30/93 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Parallel Programming Methodologies for Non-Uniform Structured...Dear Dr. van Tilborg, Enclosed you will find the annual report for " Parallel Programming Methodolo- gies for Non-Uniform Structured Problems in...Quincy Street Arlington, VA 22217-5660 Dear Dr. van Tilborg, Enclosed you will find the annual report for " Parallel Programming Methodolo- gies for Non
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
Energy Technology Data Exchange (ETDEWEB)
Gomez Enriquez, F.; Montejo Arteche, A.; Sanchez Mazon, J.; Vazquez Rodriguez, J. A.; Mendigueren Santiago, M. A.; Pacheco Baldor, M. T.; Raba Diez, J. I.
2013-07-01
To improve the traditional method of geometric adjustment of blades was a plugin from the Image J program that analyzes an image, acquired with the EPID accelerator, the way Stripe Test (test lines). The program was designed for an Elekta Accelerator model Precise, with slices of 1cm thick and a program of acquisition of images of the EPID Iview GT 3.4. At the end of the process it has resulted in the displacement, in millimeters, that needs to be done to adjust each of the blades. (Author)
Levitin-Polyak well-posedness for generalized semi-infinite multiobjective programming problems
Directory of Open Access Journals (Sweden)
Xian-Jun Long
2016-01-01
Full Text Available Abstract In this paper, we introduce a notion of Levitin-Polyak well-posedness for generalized semi-infinite multiobjective programming problems in terms of weakly efficient solutions. We obtain some metric characterizations of Levitin-Polyak well-posedness for this problem. We derive the relations between the Levitin-Polyak well-posedness and the upper semi-continuity of approximate solution maps for generalized semi-infinite multiobjective programming problems. Examples are given to illustrate our main results.
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
Directory of Open Access Journals (Sweden)
Monalisha Pattnaik
2014-12-01
Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower's functions are separable with respect to the follower's variables, and the other is that the follower's functions are convex if the follower's variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader's variable x, it is proved that the optimal solution y of the follower's mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower's programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter A, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.
Fractional Goal Programming for Fuzzy Solid Transportation Problem with Interval Cost
Directory of Open Access Journals (Sweden)
B. Radhakrishnan
2014-09-01
Full Text Available In this paper, we study a solid transportation problem with interval cost using fractional goal programming approach (FGP. In real life applications of the FGP problem with multiple objectives, it is difficult for the decision-maker(s to determine the goal value of each objective precisely as the goal values are imprecise, vague, or uncertain. Therefore, a fuzzy goal programming model is developed for this purpose. The proposed model presents an application of fuzzy goal programming to the solid transportation problem. Also, we use a special type of non-linear (hyperbolic membership functions to solve multi-objective transportation problem. It gives an optimal compromise solution. The proposed model is illustrated by using an example.
Kuhn-Tucker sufficiency for global minimum of multi-extremal mathematical programming problems
Jeyakumar, V.; Srisatkunrajah, S.; Huy, N. Q.
2007-11-01
The Kuhn-Tucker Sufficiency Theorem states that a feasible point that satisfies the Kuhn-Tucker conditions is a global minimizer for a convex programming problem for which a local minimizer is global. In this paper, we present new Kuhn-Tucker sufficiency conditions for possibly multi-extremal nonconvex mathematical programming problems which may have many local minimizers that are not global. We derive the sufficiency conditions by first constructing weighted sum of square underestimators of the objective function and then by characterizing the global optimality of the underestimators. As a consequence, we derive easily verifiable Kuhn-Tucker sufficient conditions for general quadratic programming problems with equality and inequality constraints. Numerical examples are given to illustrate the significance of our criteria for multi-extremal problems.
Application of Program Generation Technology in Solving Heat and Flow Problems
Institute of Scientific and Technical Information of China (English)
Shui Wan; Bangxian Wu; Ningning Chen
2007-01-01
Based on a new DIY concept for software development, an automatic program-generating technology attached on a software system called as Finite Element Program Generator (FEPG) provides a platform of developing programs, through which a scientific researcher can submit his special physico-mathematical problem to the system in a more direct and convenient way for solution. For solving flow and heat problems by using finite element method, the stabilization technologies and fraction-step methods are adopted to overcome the numerical difficulties caused mainly due to the dominated convection. A couple of benchmark problems are given in this paper as examples to illustrate the usage and the superiority of the automatic program generation technique, including the flow in a lid-driven cavity, the starting flow in a circular pipe, the natural convection in a square cavity, and the flow past a circular cylinder, etc. They are also shown as the verification of the algorithms.
Developing a pedagogical problem solving view for mathematics teachers with two reflection programs
Directory of Open Access Journals (Sweden)
Bracha KRAMARSKI
2009-10-01
Full Text Available The study investigated the effects of two reflection support programs on elementary school mathematics teachers’ pedagogical problem solving view. Sixty-two teachers participated in a professional development program. Thirty teachers were assigned to the self-questioning (S_Q training and thirty two teachers were assigned to the reflection discourse (R_D training. The S_Q program was based on the IMPROVE self-questioning approach which emphasizes systematic discussion along the phases of mathematical or pedagogical problem solving as student and teacher. The R_D program emphasized discussion of standard based teaching and learning principles. Findings indicated that systematic reflection support (S_Q is effective for developing mathematics PCK, and strengthening metacognitive knowledge of mathematics teachers, more than reflection discourse (R_D. No differences were found between the groups in developing beliefs about teaching mathematics in using problem solving view.
Transportation problem: A special case for linear programing problems in mining engineering
Institute of Scientific and Technical Information of China (English)
Ali Mahrous A.M.; Sik Yang Hyung
2012-01-01
In real world applications the supply,the demand and the transportation cost per unit of the quantities in a transportation problem are hardly specified precisely because of the changing economic and environmental conditions.It is also important that the time required for transportation should be minimum.In this paper a method has been proposed for the minimization of transportation costs.Supply and transportation costs per unit of the quantities are also determined.The present study was carried out to evaluate the quality of gravel to know its suitability for aggregate (raw material for concrete and road).The samples of gravel were analyzed for petrographic,physical,mechanical and chemical properties.Samples were categorized as quartzite group and carbonate group according to ASTM standard 295.Among these,samples of quartzite group were found dominant.The petrography examination of gravels which was carried out constituted of opal,tridymite,chalcedony,crystobalite and alkali carbonates rocks.Those minerals react with alkalis in cement leading to expansion and cracking of concrete.Other components such as sulfides,sulfates,halites,iron oxides,clay minerals and anhydrites are examined,which might be present as coating and impurities.The present study indicated that all samples are suitable for concrete making and obtain the optimum solution for transporting these materials from quarries to cities with minimum cost according to Egyptian Code.
Geometric Control of Patterned Linear Systems
Hamilton, Sarah C
2012-01-01
This monograph is aiming at researchers of systems control, especially those interested in multiagent systems, distributed and decentralized control, and structured systems. The book assumes no prior background in geometric control theory; however, a first year graduate course in linear control systems is desirable. Since not all control researchers today are exposed to geometric control theory, the book also adopts a tutorial style by way of examples that illustrate the geometric and abstract algebra concepts used in linear geometric control. In addition, the matrix calculations required for the studied control synthesis problems of linear multivariable control are illustrated via a set of running design examples. As such, some of the design examples are of higher dimension than one may typically see in a text; this is so that all the geometric features of the design problem are illuminated.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Rauff Lind Christensen, Tue; Klose, Andreas; Andersen, Kim Allan
are neglected in the SSFCTP. The SSFCMCTP overcome this problem by incorporating a staircase cost structure in the cost function instead of the usual one used in SSFCTP. We present a dynamic programming algorithm for the resulting problem. To enhance the performance of the generic algorithm a number......The Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem (SSFCMCTP) is a problem with versatile applications. This problem is a generalization of the Single-Sink, Fixed-Charge Transportation Problem (SSFCTP), which has a fixed-charge, linear cost structure. However, in at least two...... of enhancements is employed. The problem instance is reduced by variable pegging using a Lagrangean relaxation from which also a flow augmentation scheme is derived. Additionally a reduction in the search space is employed along with a variable transformation which generalizes a transformation known from...
Stable iterative Lagrange principle in convex programming as a tool for solving unstable problems
Kuterin, F. A.; Sumin, M. I.
2017-01-01
A convex programming problem in a Hilbert space with an operator equality constraint and a finite number of functional inequality constraints is considered. All constraints involve parameters. The close relation of the instability of this problem and, hence, the instability of the classical Lagrange principle for it to its regularity properties and the subdifferentiability of the value function in the problem is discussed. An iterative nondifferential Lagrange principle with a stopping rule is proved for the indicated problem. The principle is stable with respect to errors in the initial data and covers the normal, regular, and abnormal cases of the problem and the case where the classical Lagrange principle does not hold. The possibility of using the stable sequential Lagrange principle for directly solving unstable optimization problems is discussed. The capabilities of this principle are illustrated by numerically solving the classical ill-posed problem of finding the normal solution of a Fredholm integral equation of the first kind.
Wittek, Peter
2013-01-01
A hierarchy of semidefinite programming (SDP) relaxations approximates the global optimum of polynomial optimization problems of noncommuting variables. Generating the relaxation, however, is a computationally demanding task, and only problems of commuting variables have efficient generators. We develop an implementation for problems of noncommuting problems that creates the relaxation to be solved by SDPA -- a high-performance solver that runs in a distributed environment. We further exploit the inherent sparsity of optimization problems in quantum physics to reduce the complexity of resulting relaxation. Constrained problems with a relaxation of order two may contain up to a hundred variables. The implementation is available in C++ and Python. The tool helps solve problems such as finding the ground state energy or testing quantum correlations.
Institute of Scientific and Technical Information of China (English)
Shuo Lin; Fangjun Luan; Zhonghua Han; Xisheng Lü; Xiaofeng Zhou; Wei Liu
2014-01-01
Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems (BLPPs) are the optimization problems with hierarchical structure. In steel-making pro-duction, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment. This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.
Lima, Ricardo
2016-06-16
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Potential function methods for approximately solving linear programming problems theory and practice
Bienstock, Daniel
2002-01-01
Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.
The solution of singular optimal control problems using direct collocation and nonlinear programming
Downey, James R.; Conway, Bruce A.
1992-08-01
This paper describes work on the determination of optimal rocket trajectories which may include singular arcs. In recent years direct collocation and nonlinear programming has proven to be a powerful method for solving optimal control problems. Difficulties in the application of this method can occur if the problem is singular. Techniques exist for solving singular problems indirectly using the associated adjoint formulation. Unfortunately, the adjoints are not a part of the direct formulation. It is shown how adjoint information can be obtained from the direct method to allow the solution of singular problems.
Directory of Open Access Journals (Sweden)
Yi-hua Zhong
2013-01-01
Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
Fogle, F. R.
1994-01-01
IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.
Modeling Dynamic Programming Problems over Sequences and Trees with Inverse Coupled Rewrite Systems
Directory of Open Access Journals (Sweden)
Robert Giegerich
2014-03-01
Full Text Available Dynamic programming is a classical algorithmic paradigm, which often allows the evaluation of a search space of exponential size in polynomial time. Recursive problem decomposition, tabulation of intermediate results for re-use, and Bellman’s Principle of Optimality are its well-understood ingredients. However, algorithms often lack abstraction and are difficult to implement, tedious to debug, and delicate to modify. The present article proposes a generic framework for specifying dynamic programming problems. This framework can handle all kinds of sequential inputs, as well as tree-structured data. Biosequence analysis, document processing, molecular structure analysis, comparison of objects assembled in a hierarchic fashion, and generally, all domains come under consideration where strings and ordered, rooted trees serve as natural data representations. The new approach introduces inverse coupled rewrite systems. They describe the solutions of combinatorial optimization problems as the inverse image of a term rewrite relation that reduces problem solutions to problem inputs. This specification leads to concise yet translucent specifications of dynamic programming algorithms. Their actual implementation may be challenging, but eventually, as we hope, it can be produced automatically. The present article demonstrates the scope of this new approach by describing a diverse set of dynamic programming problems which arise in the domain of computational biology, with examples in biosequence and molecular structure analysis.
Directory of Open Access Journals (Sweden)
The Effects of Teaching Programming via Scratch on Problem Solving Skills: A Discussion from Learners' Perspective
2014-04-01
Full Text Available Computer programming is perceived as an important competence for the development of problem solving skills in addition to logical reasoning. Hence, its integration throughout all educational levels, as well as the early ages, is considered valuable and research studies are carried out to explore the phenomenon in more detail. In light of these facts, this study is an exploratory effort to investigate the effect of Scratch programming on 5th grade primary school students' problem solving skills. Moreover, the researchers wondered what 5th grade primary school students think about programming. This study was carried out in an explanatory sequential mixed methods design with the participation of 49 primary school students. According to the quantitative results, programming in Scratch platform did not cause any significant differences in the problem solving skills of the primary school students. There is only a non-significant increase in the mean of the factor of "self- confidence in their problem solving ability". When the thoughts of the primary students were considered, it can be clearly stated that all the students liked programming and wanted to improve their programming. Finally, most of the students found the Scratch platform easy to use.
Costner, Kelly Mitchell
This study developed and piloted the Problem-Solving Approach to program evaluation, which involves the direct application of the problem-solving process as a metaphor for program evaluation. A rationale for a mathematics-specific approach is presented, and relevant literature in both program evaluation and mathematics education is reviewed. The Problem-Solving Approach was piloted with a high-school level integrated course in mathematics and science that used graphing calculators and data collection devices with the goal of helping students to gain better understanding of relationships between mathematics and science. Twelve students participated in the course, which was co-taught by a mathematics teacher and a science teacher. Data collection for the evaluation included observations, a pre- and posttest, student questionnaires, student interviews, teacher interviews, principal interviews, and a focus group that involved both students and their teachers. Results of the evaluation of the course are presented as an evaluation report. Students showed improvement in their understandings of mathematics-science relationships, but also showed growth in terms of self-confidence, independence, and various social factors that were not expected outcomes. The teachers experienced a unique form of professional development by learning and relearning concepts in each other's respective fields and by gaining insights into each other's teaching strengths. Both the results of the evaluation and the evaluation process itself are discussed in light of the proposed problem-solving approach. The use of problem solving and of specific problem-solving strategies was found to be prevalent among the students and the teachers, as well as in the activities of the evaluator. Specific problem-solving strategies are highlighted for their potential value in program evaluation situations. The resulting Problem-Solving Approach, revised through the pilot application, employs problem solving as a
Integer Programming Formulation of the Problem of Generating Milton Babbitt's All-partition Arrays
DEFF Research Database (Denmark)
Tanaka, Tsubasa; Bemman, Brian; Meredith, David
2016-01-01
integer partition of 12. Integer programming (IP) has proven to be effective for solving such combinatorial prob- lems, however, it has never before been applied to the problem addressed in this paper. We introduce a new way of viewing this problem as one in which restricted overlaps between integer......Milton Babbitt (1916–2011) was a composer of twelve-tone serial music noted for creating the all-partition array. The problem of generating an all-partition array involves finding a rectangular array of pitch-class integers that can be partitioned into regions, each of which represents a distinct...... partition regions are allowed. This permits us to describe the problem using a set of linear constraints necessary for IP. In particular, we show that this problem can be defined as a special case of the well-known problem of set-covering (SCP), modified with additional constraints. Due to the difficulty...
EXACT AUGMENTED LAGRANGIAN FUNCTION FOR NONLINEAR PROGRAMMING PROBLEMS WITH INEQUALITY CONSTRAINTS
Institute of Scientific and Technical Information of China (English)
DU Xue-wu; ZHANG Lian-sheng; SHANG You-lin; LI Ming-ming
2005-01-01
An exact augmented Lagrangian function for the nonlinear nonconvex programming problems with inequality constraints was discussed. Under suitable hypotheses, the relationship was established between the local unconstrained minimizers of the augmented Lagrangian function on the space of problem variables and the local minimizers of the original constrained problem. Furthermore, under some assumptions,the relationship was also established between the global solutions of the augmented Lagrangian function on some compact subset of the space of problem variables and the global solutions of the constrained problem. Therefore, from the theoretical point of view, a solution of the inequality constrained problem and the corresponding values of the Lagrange multipliers can be found by the well-known method of multipliers which resort to the unconstrained minimization of the augmented Lagrangian function presented.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
Directory of Open Access Journals (Sweden)
Paras Bhatnagar
2012-10-01
Full Text Available Kaul and Kaur [7] obtained necessary optimality conditions for a non-linear programming problem by taking the objective and constraint functions to be semilocally convex and their right differentials at a point to be lower semi-continuous. Suneja and Gupta [12] established the necessary optimality conditions without assuming the semilocal convexity of the objective and constraint functions but their right differentials at the optimal point to be convex. Suneja and Gupta [13] established necessary optimality conditions for an efficient solution of a multiobjective non-linear programming problem by taking the right differentials of the objective functions and constraintfunctions at the efficient point to be convex. In this paper we obtain some results for a properly efficient solution of a multiobjective non-linear fractional programming problem involving semilocally convex and related functions by assuming generalized Slater type constraint qualification.
Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation
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R. T. N. Cardoso
2013-01-01
Full Text Available A heuristic algorithm is proposed for a class of stochastic discrete-time continuous-variable dynamic programming problems submitted to non-Gaussian disturbances. Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. Thus, decision makers are able to choose any quantile they wish. This new idea is carried out by using Monte Carlo simulations embedded in an approximate algorithm proposed to deterministic dynamic programming problems. The new method is tested in instances of the classical inventory control problem. The results obtained attest for the efficiency and efficacy of the algorithm in solving these important stochastic optimization problems.
Co-evolutionary algorithm: An efficient approach for bilevel programming problems
Li, Hecheng; Fang, Lei
2014-03-01
The bilevel programming problem involves two optimization problems, which is hierarchical, strongly NP-hard and very challenging for most existing optimization approaches. An efficient universal co-evolutionary algorithm is developed in this article to deal with various bilevel programming problems. In the proposed algorithm, evolutionary algorithms are used to explore the leader's and the follower's decision-making spaces interactively. Unlike other existing approaches, in the suggested procedure the follower's problem is solved in two phases. First, an evolutionary algorithm is run for a few generations to obtain an approximation of lower level solutions. In the second phase, from all approximate solutions obtained above, only a small number of good points are selected and evolved again by a newly designed multi-criteria evolutionary algorithm. The technique refines some candidate solutions and can efficiently reduce the computational cost of obtaining feasible solutions. Proof-of-principle experiments demonstrate the efficiency of the proposed approach.
A high performance neural network for solving nonlinear programming problems with hybrid constraints
Tao, Qing; Cao, Jinde; Xue, Meisheng; Qiao, Hong
2001-09-01
A continuous neural network is proposed in this Letter for solving optimization problems. It not only can solve nonlinear programming problems with the constraints of equality and inequality, but also has a higher performance. The main advantage of the network is that it is an extension of Newton's gradient method for constrained problems, the dynamic behavior of the network under special constraints and the convergence rate can be investigated. Furthermore, the proposed network is simpler than the existing networks even for solving positive definite quadratic programming problems. The network considered is constrained by a projection operator on a convex set. The advanced performance of the proposed network is demonstrated by means of simulation of several numerical examples.
Geometrization of Trace Formulas
Frenkel, Edward
2010-01-01
Following our joint work arXiv:1003.4578 with Robert Langlands, we make the first steps toward developing geometric methods for analyzing trace formulas in the case of the function field of a curve defined over a finite field. We also suggest a conjectural framework of geometric trace formulas for curves defined over the complex field, which exploits the categorical version of the geometric Langlands correspondence.
Forneris, Tanya; Danish, Steven J; Scott, David L
2007-01-01
The Going for the Goal (GOAL) program is designed to teach adolescents life skills. There have been few efforts to assess whether the skills that GOAL is designed to teach are being learned by adolescents involved in the program. The purpose of this study was to examine the impact of GOAL on the acquisition of skills in the areas of setting goals, solving problems, and seeking social support. Interviews were conducted with twenty adolescents. Those who participated in GOAL reported that they had learned how to set goals, to solve problems effectively, and to seek the appropriate type of social support.
The Knowledge of Expert Opinion in Intuitionistic Fuzzy Linear Programming Problem
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A. Nagoorgani
2015-01-01
Full Text Available In real life, information available for certain situations is vague and such uncertainty is unavoidable. One possible solution is to consider the knowledge of experts on the parameters involved as intuitionistic fuzzy data. We examine a linear programming problem in which all the coefficients are intuitionistic in nature. An approach is presented to solve an intuitionistic fuzzy linear programming problem. In this proposed approach, a procedure for allocating limited resources effectively among competing demands is developed. An example is given to highlight the illustrated study.
A novel approach based on preference-based index for interval bilevel linear programming problem.
Ren, Aihong; Wang, Yuping; Xue, Xingsi
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
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Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
Institute of Scientific and Technical Information of China (English)
Qin Ni; Ch. Zillober; K. Schittkowski
2005-01-01
In this paper, we describe a method to solve large-scale structural optimization problems by sequential convex programming (SCP). A predictor-corrector interior point method is applied to solve the strictly convex subproblems. The SCP algorithm and the topology optimization approach are introduced. Especially, different strategies to solve certain linear systems of equations are analyzed. Numerical results are presented to show the efficiency of the proposed method for solving topology optimization problems and to compare different variants.
Stress-constrained truss topology optimization problems that can be solved by linear programming
DEFF Research Database (Denmark)
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....
An Approach for Solving Goal Programming Problems using Interval Type-2 Fuzzy Goals
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Juan Carlos Figueroa-García
2015-08-01
Full Text Available This paper presents a proposal for solving goal problems involving multiple experts opinions and perceptions. In goal programming problems where no statistical data about their goals exist, the use of information coming from experts becomes the last reliable source. This way, we propose an approach to model this kind of goals using Interval Type-2 fuzzy sets, and a simple method for finding an optimal solution based on previous methods that have been proposed for classical fuzzy sets.
Institute of Scientific and Technical Information of China (English)
HUANG Hui; FEI Pu-sheng; YUAN Yuan
2005-01-01
A primal-dual infeasible-interior-point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm,moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness.
Hybrid constraint programming and metaheuristic methods for large scale optimization problems
2011-01-01
This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatori...
Institute of Scientific and Technical Information of China (English)
Wan Zhongping; Wang Guangrain; Lv Yibing
2011-01-01
The penalty function method, presented many years ago, is an important nu- merical method for the mathematical programming problems. In this article, we propose a dual-relax penalty function approach, which is significantly different from penalty func- tion approach existing for solving the bilevel programming, to solve the nonlinear bilevel programming with linear lower level problem. Our algorithm will redound to the error analysis for computing an approximate solution to the bilevel programming. The error estimate is obtained among the optimal objective function value of the dual-relax penalty problem and of the original bilevel programming problem. An example is illustrated to show the feasibility of the proposed approach.
Geometric optimization and sums of algebraic functions
Vigneron, Antoine E.
2014-01-01
We present a new optimization technique that yields the first FPTAS for several geometric problems. These problems reduce to optimizing a sum of nonnegative, constant description complexity algebraic functions. We first give an FPTAS for optimizing such a sum of algebraic functions, and then we apply it to several geometric optimization problems. We obtain the first FPTAS for two fundamental geometric shape-matching problems in fixed dimension: maximizing the volume of overlap of two polyhedra under rigid motions and minimizing their symmetric difference. We obtain the first FPTAS for other problems in fixed dimension, such as computing an optimal ray in a weighted subdivision, finding the largest axially symmetric subset of a polyhedron, and computing minimum-area hulls.
Institute of Scientific and Technical Information of China (English)
Qin Ni
2001-01-01
An NGTN method was proposed for solving large-scale sparse nonlinear programming (NLP) problems. This is a hybrid method of a truncated Newton direction and a modified negative gradient direction, which is suitable for handling sparse data structure and possesses Q-quadratic convergence rate. The global convergence of this new method is proved,the convergence rate is further analysed, and the detailed implementation is discussed in this paper. Some numerical tests for solving truss optimization and large sparse problems are reported. The theoretical and numerical results show that the new method is efficient for solving large-scale sparse NLP problems.
A two-phase linear programming approach for redundancy allocation problems
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Hsieh Yi-Chih
2002-01-01
Full Text Available Provision of redundant components in parallel is an efficient way to increase the system reliability, however, the weight, volume and cost of the system will increase simultaneously. This paper proposes a new two-phase linear programming approach for solving the nonlinear redundancy allocation problems subject to multiple linear constraints. The first phase is used to approximately allocate the resource by using a general linear programming, while the second phase is used to re-allocate the slacks of resource by using a 0-1 integer linear programming. Numerical results demonstrate the effectiveness and efficiency of the proposed approach.
Dynamic programming for infinite horizon boundary control problems of PDE's with age structure
Faggian, Silvia
2008-01-01
We develop the dynamic programming approach for a family of infinite horizon boundary control problems with linear state equation and convex cost. We prove that the value function of the problem is the unique regular solution of the associated stationary Hamilton--Jacobi--Bellman equation and use this to prove existence and uniqueness of feedback controls. The idea of studying this kind of problem comes from economic applications, in particular from models of optimal investment with vintage capital. Such family of problems has already been studied in the finite horizon case by Faggian. The infinite horizon case is more difficult to treat and it is more interesting from the point of view of economic applications, where what mainly matters is the behavior of optimal trajectories and controls in the long run. The study of infinite horizon is here performed through a nontrivial limiting procedure from the corresponding finite horizon problem.
Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming
Claudel, Christian G.
2014-01-01
This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.
Exploring New Geometric Worlds
Nirode, Wayne
2015-01-01
When students work with a non-Euclidean distance formula, geometric objects such as circles and segment bisectors can look very different from their Euclidean counterparts. Students and even teachers can experience the thrill of creative discovery when investigating these differences among geometric worlds. In this article, the author describes a…
J.I. van Hemert; C. Solnon
2004-01-01
textabstractWe compare two heuristic approaches, evolutionary computation and ant colony optimisation, and a complete tree-search approach, constraint programming, for solving binary constraint satisfaction problems. We experimentally show that, if evolutionary computation is far from being able to
ALI KHAN, ANSAR
THE AUTHOR DISCUSSES THE NEED FOR FUNCTIONAL, SEQUENTIAL PROGRAMS OF LITERACY, VOCATIONAL, LIBERAL, POLITICAL, AND HUMAN RELATIONS EDUCATION IN RURAL AREAS OF PAKISTAN. PROBLEMS AND CHALLENGES ARE SEEN IN THE OCCUPATIONAL CASTE SYSTEM, FAMILY STRUCTURES, ATTITUDES TOWARD THE EDUCATION OF BOYS AND GIRLS, POOR MEANS OF TRANSPORTATION AND…
Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables
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S. K. Barik
2012-01-01
Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.
Kalelioglu, Filiz; Gülbahar, Yasemin
2014-01-01
Computer programming is perceived as an important competence for the development of problem solving skills in addition to logical reasoning. Hence, its integration throughout all educational levels, as well as the early ages, is considered valuable and research studies are carried out to explore the phenomenon in more detail. In light of these…
A note on solving large-scale zero-one programming problems
Adema, Jos J.
1988-01-01
A heuristic for solving large-scale zero-one programming problems is provided. The heuristic is based on the modifications made by H. Crowder et al. (1983) to the standard branch-and-bound strategy. First, the initialization is modified. The modification is only useful if the objective function valu
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X. Zhao
2012-01-01
Full Text Available A combined interior point homotopy continuation method is proposed for solving general multiobjective programming problem. We prove the existence and convergence of a smooth homotopy path from almost any interior initial interior point to a solution of the KKT system under some basic assumptions.
A new gradient-based neural network for solving linear and quadratic programming problems.
Leung, Y; Chen, K Z; Jiao, Y C; Gao, X B; Leung, K S
2001-01-01
A new gradient-based neural network is constructed on the basis of the duality theory, optimization theory, convex analysis theory, Lyapunov stability theory, and LaSalle invariance principle to solve linear and quadratic programming problems. In particular, a new function F(x, y) is introduced into the energy function E(x, y) such that the function E(x, y) is convex and differentiable, and the resulting network is more efficient. This network involves all the relevant necessary and sufficient optimality conditions for convex quadratic programming problems. For linear programming and quadratic programming (QP) problems with unique and infinite number of solutions, we have proven strictly that for any initial point, every trajectory of the neural network converges to an optimal solution of the QP and its dual problem. The proposed network is different from the existing networks which use the penalty method or Lagrange method, and the inequality constraints are properly handled. The simulation results show that the proposed neural network is feasible and efficient.
Sensitivity analysis of efficient solution in vector MINMAX boolean programming problem
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Vladimir A. Emelichev
2002-07-01
Full Text Available We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal solution preserves optimality was obtained. MSC: 90C29, 90C31
A note on solving large-scale zero-one programming problems
Adema, Jos J.
1988-01-01
A heuristic for solving large-scale zero-one programming problems is provided. The heuristic is based on the modifications made by H. Crowder et al. (1983) to the standard branch-and-bound strategy. First, the initialization is modified. The modification is only useful if the objective function valu
Comparison of Cursive Handwriting Instruction Programs among Students without Identified Problems
Shimel, Kristin; Candler, Catherine; Neville-Smith, Marsha
2009-01-01
The purpose of this study was to compare the effects of cursive handwriting programs in improving letter legibility and form in third-grade students without identified handwriting problems. Four months into the school year, cursive handwriting was assessed for a sample of convenience of 50 third-grade students. Subsequently, students received…
Keeping Fit with Asta O'Donnell. An Exercise Program for Problem Backs.
O'Donnell, Asta
An estimated 75 million people in the United States suffer from some type of back problem. Most are caused by muscle strain and improper posture. This book describes an exercise program designed to relieve muscle strain, improve and correct posture, and reduce stress and tension. The book is divided into four sections: "Warm…
A note on solving large-scale zero-one programming problems
Adema, Jos J.
1988-01-01
A heuristic for solving large-scale zero-one programming problems is provided. The heuristic is based on the modifications made by H. Crowder et al. (1983) to the standard branch-and-bound strategy. First, the initialization is modified. The modification is only useful if the objective function
Enhancing Problem-Solving Capabilities Using Object-Oriented Programming Language
Unuakhalu, Mike F.
2009-01-01
This study integrated object-oriented programming instruction with transfer training activities in everyday tasks, which might provide a mechanism that can be used for efficient problem solving. Specifically, a Visual BASIC embedded with everyday tasks group was compared to another group exposed to Visual BASIC instruction only. Subjects were 40…
Connectedness of G-proper Efficient Solution Set for Multiobjective Programming Problem
Institute of Scientific and Technical Information of China (English)
KONG Xiang-qing
2002-01-01
In this paper, we investigate the connectedness of G-proper efficient solution set for multiobjective programming problem. It is shown that the G-proper efficient solution set is connected if objective functions are convex. A sufficient condition for the connectedness of G-proper efficient solution set is established when objective functions are strictly quasiconvex.
Havighurst, Sophie S.; Wilson, Katherine R.; Harley, Ann E.; Kehoe, Christiane; Efron, Daryl; Prior, Margot R.
2013-01-01
This study evaluated a 6-session group parenting program, "Tuning into Kids" (TIK), as treatment for young children (aged 4.0-5.11 years) with behavior problems. TIK targets parent emotion socialization (parent emotion awareness, regulation and emotion coaching skills). Fifty-four parents, recruited via a child behavior clinic, were randomized…
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Dalbinder Kour
2015-12-01
Full Text Available This paper focuses on solving the transportation problems with neutrosophic data for the first time. The indeterminacy factor has been considered in Transportation Problems (TP. The two methods of linear programming – Fuzzy Linear Programming (FLP and Crisp Linear Programming (CLP are discussed with reference to neutrosophic transportation problems. The first method uses the membership, non-membership and indeterminacy degrees separately to find the crisp solution using the Fuzzy Programming Technique and then the optimal solution is calculated in terms of neutrosophic data with the help of defined cost membership functions. The satisfaction degree is then calculated to check the better solution. The second method directly solves the TP to find crisp solution considering a single objective function. The cost objective function is taken as neutrosophic data and the methods have been used as such for the first time. Both the methods have been illustrated with the help of a numerical example and these are then applied to solve a real life multi - objective and multi-index transportation problem. Finally the results are compared.
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S. F. Tantawy
2007-01-01
Full Text Available We presented a feasible direction method to find all optimal extreme points for the linear programming problem. Our method depends on the conjugate gradient projection method starting with an initial point we generate a sequence of feasible directions towards all alternative extremes.
The Special Caretakers Program: A Hospital's Solution to the Boarder Baby Problem.
Gentry, Linda R.
1993-01-01
Describes Special Caretakers Program, project in which employees of Hahnemann University Hospital in Philadelphia (Pennsylvania) became foster parents for hospital's boarder babies, newborns and children medically ready for discharge who often waited weeks or months for appropriate foster home. Discusses problems and solutions encountered in the…
Geometric Associative Memories and Their Applications to Pattern Classification
Cruz, Benjamin; Barron, Ricardo; Sossa, Humberto
Associative memories (AMs) were proposed as tools usually used in the restoration and classification of distorted patterns. Many interesting models have emerged in the last years with this aim. In this chapter a novel associative memory model (Geometric Associative Memory, GAM) based on Conformal Geometric Algebra (CGA) principles is described. At a low level, CGA provides a new coordinate-free framework for numeric processing in problem solving. The proposed model makes use of CGA and quadratic programming to store associations among patterns and their respective class. To classify an unknown pattern, an inner product is applied between it and the obtained GAM. Numerical and real examples to test the proposal are given. Formal conditions are also provided that assure the correct functioning of the proposal.
Conrad, Patricia A; Hird, Dave; Arzt, Jonathan; Hayes, Rick H; Magliano, Dave; Kasper, Janine; Morfin, Saul; Pinney, Stephen
2007-01-01
This article describes a computerized case-based CD-ROM (CD) on international animal health that was developed to give veterinary students an opportunity to "virtually" work alongside veterinarians and other veterinary students as they try to solve challenging disease problems relating to tuberculosis in South African wildlife, bovine abortion in Mexico, and neurologic disease in horses in Rapa Nui, Chile. Each of the three case modules presents, in a highly interactive format, a problem or mystery that must be solved by the learner. As well as acquiring information via video clips and text about the specific health problem, learners obtain information about the different countries, animal-management practices, diagnostic methods, related disease-control issues, economic factors, and the opinions of local experts. After assimilating this information, the learner must define the problem and formulate an action plan or make a recommendation or diagnosis. The computerized program invokes three principles of adult education: active learning, learner-centered education, and experiential learning. A medium that invokes these principles is a potentially efficient learning tool and template for developing other case-based problem-solving computerized programs. The program is accessible on the World Wide Web at International_web/international_menu.html>. A broadband Internet connection is recommended, since the modules make extensive use of embedded video and audio clips. Information on how to obtain the CD is also provided.
Directory of Open Access Journals (Sweden)
Samir Dey
2015-07-01
Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.
Indian Academy of Sciences (India)
ALI EBRAHIMNEJAD
2016-03-01
Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at destinations using available supplies at origins in a crisp environment. In real life situations, the decision maker may not be sure about the precise values of the coefficients belonging to the transportation problem. The aim of this paper is to introduce a formulation of TP involving interval-valued trapezoidal fuzzy numbers for the transportation costs and values of supplies and demands. We propose a fuzzy linear programming approach for solvinginterval-valued trapezoidal fuzzy numbers transportation problem based on comparison of interval-valued fuzzy numbers by the help of signed distance ranking. To illustrate the proposed approach an application example issolved. It is demonstrated that study of interval-valued trapezoidal fuzzy numbers transportation problem gives rise to the same expected results as those obtained for TP with trapezoidal fuzzy numbers.
A physics perspective on geometric Langlands duality
Schlesinger, Karl-Georg
2009-01-01
We review the approach to the geometric Langlands program for algebraic curves via S-duality of an N=4 supersymmetric four dimensional gauge theory, initiated by Kapustin and Witten in 2006. We sketch some of the central further developments. Placing this four dimensional gauge theory into a six dimensional framework, as advocated by Witten, holds the promise to lead to a formulation which makes geometric Langlands duality a manifest symmetry (like coavariance in differential geometry). Furthermore, it leads to an approach toward geometric Langlands duality for algebraic surfaces, reproducing and extending the recent results of Braverman and Finkelberg.
The Strengthening Families Program 10-14: influence on parent and youth problem-solving skill.
Semeniuk, Y; Brown, R L; Riesch, S K; Zywicki, M; Hopper, J; Henriques, J B
2010-06-01
The aim of this paper is to report the results of a preliminary examination of the efficacy of the Strengthening Families Program (SFP) 10-14 in improving parent and youth problem-solving skill. The Hypotheses in this paper include: (1) youth and parents who participated in SFP would have lower mean scores immediately (T2) and 6 months (T3) post intervention on indicators of hostile and negative problem-solving strategies; (2) higher mean scores on positive problem-solving strategies; and (3) youth who participated in SFP would have higher mean scores at T2 and at T3 on indicators of individual problem solving and problem-solving efficacy than youth in the comparison group. The dyads were recruited from elementary schools that had been stratified for race and assigned randomly to intervention or comparison conditions. Mean age of youth was 11 years (SD = 1.04). Fifty-seven dyads (34-intervention&23-control) were videotaped discussing a frequently occurring problem. The videotapes were analysed using the Iowa Family Interaction Rating Scale (IFIRS) and data were analysed using Dyadic Assessment Intervention Model. Most mean scores on the IFIRS did not change. One score changed as predicted: youth hostility decreased at T3. Two scores changed contrary to prediction: parent hostility increased T3 and parent positive problem solving decreased at T2. SFP demonstrated questionable efficacy for problem-solving skill in this study.
The Strengthening Families Program 10–14: influence on parent and youth problem-solving skill
Semeniuk, Y.; Brown, R. L.; Riesch, S.K.; Zywicki, M.; Hopper, J.; Henriques, J.B.
2011-01-01
The aim of this paper is to report the results of a preliminary examination of the efficacy of the Strengthening Families Program (SFP) 10–14 in improving parent and youth problem-solving skill. The Hypotheses in this paper include: (1) youth and parents who participated in SFP would have lower mean scores immediately (T2) and 6 months (T3) post intervention on indicators of hostile and negative problem-solving strategies; (2) higher mean scores on positive problem-solving strategies; and (3) youth who participated in SFP would have higher mean scores at T2 and at T3 on indicators of individual problem solving and problem-solving efficacy than youth in the comparison group. The dyads were recruited from elementary schools that had been stratified for race and assigned randomly to intervention or comparison conditions. Mean age of youth was 11 years (SD = 1.04). Fifty-seven dyads (34-intervention & 23-control) were videotaped discussing a frequently occurring problem. The videotapes were analysed using the Iowa Family Interaction Rating Scale (IFIRS) and data were analysed using Dyadic Assessment Intervention Model. Most mean scores on the IFIRS did not change. One score changed as predicted: youth hostility decreased at T3. Two scores changed contrary to prediction: parent hostility increased T3 and parent positive problem solving decreased at T2. SFP demonstrated questionable efficacy for problem-solving skill in this study. PMID:20584236
Producing Television Agriculture Program: Issues and Problems among Malaysian Television Producers
Directory of Open Access Journals (Sweden)
Md. S. Hassan
2010-01-01
Full Text Available Problem statement: One of the developing sectors in Malaysia is agriculture. Agriculture doubtlessly has assisted this country in terms of enhancing the economic level, offering a huge number of employment opportunities and uplifting the socio-economy status of the community. To ensure the sustainability of this sector to the country, we must ensure that the valuable agriculture information is continuously provided to the public and the information must be disseminated through the most effective channel. Here, television can be the mean channel. Approach: This study aimed to investigate the issues raised and problems faced by the Malaysian agriculture television program producers in producing the television agriculture programs. Data was collected using an in-depth interview among three agriculture television producers in Malaysia. The questions served as a guide, but allowed respondents freedom and flexibility in their answers. The findings were in the form of descriptive analysis. Results: Based on the analysis done, it can be concluded that the cooperation between Radio Television Malaysia and Department of Agriculture Malaysia is important to ensure the success and continuity of the agriculture programs. It was found that the agriculture programs were evaluated internally by the Radio Television Malaysia auditor and externally by AGB Nielsen. The producers also received feedback from their local and foreign audience in the form of e-mail and telephone. Human resource, transportation and financial are the main problems that need to be overcome by the producers. Conclusion/Recommendations: It is suggested that other media organizations and giant agriculture companies can join RTM in producing agriculture programs. This can aid RTM in producing more innovative agriculture programs and can attract the youth to watch the program.
On the Performance of Different Genetic Programming Approaches for the SORTING Problem.
Wagner, Markus; Neumann, Frank; Urli, Tommaso
2015-01-01
In genetic programming, the size of a solution is typically not specified in advance, and solutions of larger size may have a larger benefit. The flexibility often comes at the cost of the so-called bloat problem: individuals grow without providing additional benefit to the quality of solutions, and the additional elements can block the optimization process. Consequently, problems that are relatively easy to optimize cannot be handled by variable-length evolutionary algorithms. In this article, we analyze different single- and multiobjective algorithms on the sorting problem, a problem that typically lacks independent and additive fitness structures. We complement the theoretical results with comprehensive experiments to indicate the tightness of existing bounds, and to indicate bounds where theoretical results are missing.
Geometric and Texture Inpainting by Gibbs Sampling
DEFF Research Database (Denmark)
Gustafsson, David Karl John; Pedersen, Kim Steenstrup; Nielsen, Mads
2007-01-01
This paper discuss a method suitable for inpainting both large scale geometric structures and more stochastic texture components. Image inpainting concerns the problem of reconstructing the intensity contents inside regions of missing data. Common techniques for solving this problem are methods...
State of art and key problems of OOP for FE programming in engineering analysis
Li, Heng; Zhou, Yunyun
2013-03-01
Object-oriented programming (OOP) has been the most important development method, especially for huge and complicated program systems, since OOP can overcome structural complexity of code, strong coupling among modules and poor maintenance shortcomings in traditional structural programming. Since B.W.R.Forde applied OOP to Finite Element (FE) firstly in 1990, the research in this field has not been stopped. Scholars have taken many positive and useful attempts on study of OOP in FE programming from different aspects. The state of the art of OOP in FE and current development has been reviewed, and the key problems in the OOP FEM fields thus are pointed out, thus prospects of OOP in FE code design are put forward.
Geometric and unipotent crystals
Berenstein, Arkady; Kazhdan, David
1999-01-01
In this paper we introduce geometric crystals and unipotent crystals which are algebro-geometric analogues of Kashiwara's crystal bases. Given a reductive group G, let I be the set of vertices of the Dynkin diagram of G and T be the maximal torus of G. The structure of a geometric G-crystal on an algebraic variety X consists of a rational morphism \\gamma:X-->T and a compatible family e_i:G_m\\times X-->X, i\\in I of rational actions of the multiplicative group G_m satisfying certain braid-like ...
Stability of multi-objective bi-level linear programming problems under fuzziness
Directory of Open Access Journals (Sweden)
Abo-Sinna Mahmoud A.
2013-01-01
Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.
Institute of Scientific and Technical Information of China (English)
李丹; 戎蒙恬; 殳国华
2011-01-01
探讨了几何规划在基于短沟道模型的互补金属氧化物半导体(CMOS)电路中的应用.首先采用Level 1模型得到电路的初始规划,然后将所得元件值代入Hspice仿真程序,再从仿真输出的列表文件中取出各CMOS管的静态电压电流变量和等效小信号模型参数.将它们代入以修正因子为规划变量的几何规划算法,在前一次工作点附近搜索本次的最优设计.修正后的电路再次进行Hspice仿真.几何规划和仿真反复交替进行,直到最优化的目标值稳定.模拟集成电路的仿真实例表明,算法对短沟道模型电路是有效的.%A method of applying geometric programming to complementary metal oxide semiconductor (CMOS) based on short-channel models is described. An original solution based on Level 1 model via geometric programming is obtained first. Then simulate the original circuit by Hspice and acquire important parameters of all CMOS transistors from the output list file. These parameters are used in adjusting software to search the adjusting factors and achieve a new solution near the previous one. Simulating and geometric programming iteratively until the objective of optimization keeps stable. A simulation example proves the algorithm is effective in short-channel techniques.
Wegmann, Lena; Bühler, Anneke; Strunk, Mareike; Lang, Peter; Nowak, Dennis
2012-04-01
This study examines whether individual differences in impulsivity and emotional problems in adolescent smokers are related to initial smoking characteristics of participants, acceptance, retention and outcome of a school-based smoking cessation program. The data was obtained from a feasibility study of a youth-specific, cognitive-behavioral and motivation enhancing program at 22 schools with 139 participating teenage smokers in Germany. A one-group-pre-posttest design was realized. Impulsivity levels were assessed by use of the impulsivity scale of the IVE ("Inventar zur Erfassung von Impulsivität, Risikoverhalten und Empathie", Stadler, Janke, & Schmeck, 2004). To evaluate the extent of emotional problems, the corresponding 5-items scale of the SDQ-Deu ("Strength and difficulties questionnaire", Klasen et al., 2000) was applied. Smoking behavior and acceptance of the program were assessed by students' self-reports. Acceptance and retention did not differ with regard to impulsivity and emotional problems, but initial smoking status did. Cessation rates varied with level of impulsivity: compared to non-impulsive participants, impulsive adolescents succeeded in quitting smoking less often. Emotional problems were not related to the rate of quitting. Impulsive adolescents were similarly compliant to the offered cessation intervention as less impulsive smokers. In spite of their general positive evaluation, impulsive adolescents seem to benefit less from a smoking cessation program than their non-impulsive counterparts. Specific elements supporting impulsive teenage smokers in their goal to quit should be incorporated into youth-specific cessation programs. Copyright © 2011 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Glass, Micheal W.; Hogan, Roy E., Jr.; Gartling, David K.
2010-03-01
The need for the engineering analysis of systems in which the transport of thermal energy occurs primarily through a conduction process is a common situation. For all but the simplest geometries and boundary conditions, analytic solutions to heat conduction problems are unavailable, thus forcing the analyst to call upon some type of approximate numerical procedure. A wide variety of numerical packages currently exist for such applications, ranging in sophistication from the large, general purpose, commercial codes, such as COMSOL, COSMOSWorks, ABAQUS and TSS to codes written by individuals for specific problem applications. The original purpose for developing the finite element code described here, COYOTE, was to bridge the gap between the complex commercial codes and the more simplistic, individual application programs. COYOTE was designed to treat most of the standard conduction problems of interest with a user-oriented input structure and format that was easily learned and remembered. Because of its architecture, the code has also proved useful for research in numerical algorithms and development of thermal analysis capabilities. This general philosophy has been retained in the current version of the program, COYOTE, Version 5.0, though the capabilities of the code have been significantly expanded. A major change in the code is its availability on parallel computer architectures and the increase in problem complexity and size that this implies. The present document describes the theoretical and numerical background for the COYOTE program. This volume is intended as a background document for the user's manual. Potential users of COYOTE are encouraged to become familiar with the present report and the simple example analyses reported in before using the program. The theoretical and numerical background for the finite element computer program, COYOTE, is presented in detail. COYOTE is designed for the multi-dimensional analysis of nonlinear heat conduction
Tikhonov regularization and constrained quadratic programming for magnetic coil design problems
Directory of Open Access Journals (Sweden)
Garda Bartłomiej
2014-06-01
Full Text Available In this work, the problem of coil design is studied. It is assumed that the structure of the coil is known (i.e., the positions of simple circular coils are ﬁxed and the problem is to ﬁnd current distribution to obtain the required magnetic ﬁeld in a given region. The unconstrained version of the problem (arbitrary currents are allowed can be formulated as a Least-SQuares (LSQ problem. However, the results obtained by solving the LSQ problem are usually useless from the application point of view. Moreover, for higher dimensions the problem is ill-conditioned. To overcome these difﬁculties, a regularization term is sometimes added to the cost function, in order to make the solution smoother. The regularization technique, however, produces suboptimal solutions. In this work, we propose to solve the problem under study using the constrained Quadratic Programming (QP method. The methods are compared in terms of the quality of the magnetic ﬁeld obtained, and the power of the designed coil. Several 1D and 2D examples are considered. It is shown that for the same value of the maximum current the QP method provides solutions with a higher quality magnetic ﬁeld than the regularization method.
Effects of a conditional cash transfer program on children's behavior problems.
Ozer, Emily J; Fernald, Lia C H; Manley, James G; Gertler, Paul J
2009-04-01
Governments are increasingly using conditional cash transfer programs to reduce the negative effects of poverty on children's development. These programs have demonstrated benefits for children's nutrition and physical development, but the effect of conditional cash transfers on children's behaviors has not been systematically evaluated. The objective of this study was to evaluate the effects of a conditional cash transfer on children's behavior by using a quasi-experimental design. In 1997, the Mexican government initiated a large-scale conditional cash transfer (Oportunidades) in 506 very poor rural communities. Oportunidades provided cash transfers that were contingent on visits to medical practitioners, consumption of nutritional supplementation, and school enrollment. In 2003, an assessment of 4- to 6-year-old children in these households was conducted, and outcomes were compared with children from 152 additional poor rural communities who had been recruited by using rigorous matching procedures. The primary outcome measure for this analysis was maternal report of behavior problems in terms of anxiety/depressive and aggressive/oppositional symptoms. Analyses reported here compared 778 children from beneficiary households who had received 3.5 to 5.0 years of exposure to the program and a comparison group of 263 children who had received no exposure to the program at the time of assessment but whose families later enrolled in the program. Participation in Oportunidades was associated with a 10% decrement in aggressive/oppositional symptoms but was not associated with significant decrements in anxiety/depressive symptoms or total problem behaviors while controlling for covariates. Effects of treatment did not differ by children's gender or ethnicity. Although this large-scale conditional cash transfer program for poor Mexican families did not directly address children's behavior problems, it found evidence of indirect effects on children's behavior. Results
Directory of Open Access Journals (Sweden)
A.V. Degtyarev
2013-10-01
Full Text Available In this article, deviant behavior is considered as a combination of different manifestations of personality, leading eventually to its social desaptation. It is shown that an effective method of preventing deviant behavior is psychological training. Group training activity helps to solve the problems associated with the development of various behavioral skills, to provide psychological support, and can be used as a means of psychological work with teenagers with behavioral problems. We discuss the basic points required to effectively create and conduct training programs in general, as well as the challenges and opportunities of designing trainings in order to develop emotional intelligence as a method of prevention of deviant behavior
Institute of Scientific and Technical Information of China (English)
Zi-Luan Wei
2002-01-01
A regular splitting and potential reduction method is presented for solving a quadratic programming problem with box constraints (QPB) in this paper. A general algorithm is designed to solve the QPB problem and generate a sequence of iterative points. We show that the number of iterations to generate an e-minimum solution or an e-KKT solution by the algorithm is bounded by O O(n2/∈log1/∈+nlong(1+√2n) and the total running time is bounded by O(n2(n + logn +log1/∈ )(n/∈log1/∈ + logn) ) arithmetic operations.
Observations on the linear programming formulation of the single reflector design problem.
Canavesi, Cristina; Cassarly, William J; Rolland, Jannick P
2012-02-13
We implemented the linear programming approach proposed by Oliker and by Wang to solve the single reflector problem for a point source and a far-field target. The algorithm was shown to produce solutions that aim the input rays at the intersections between neighboring reflectors. This feature makes it possible to obtain the same reflector with a low number of rays - of the order of the number of targets - as with a high number of rays, greatly reducing the computation complexity of the problem.
PROBLEMS AND POSSIBLE SOLUTIONS IN CHILDREN’S ENGLISH TEACHING PROGRAM
Institute of Scientific and Technical Information of China (English)
Zhao; Xiufeng
1999-01-01
This paper intends to give a brief introduction to the overall English teaching program to chil-dren.It analyses the problems related to the program.Scarcity of qualified teachers,of unified supervi-sion and national control,exam-orientedness and age inappropriateness are found to he the primary fac-tors affecting children’s second language acquisition.It puts forward some suggestions for the improve-ment of children’s English teaching in terms of conceptions and practices.
Energy Technology Data Exchange (ETDEWEB)
Kim, D.; Ghanem, R. [State Univ. of New York, Buffalo, NY (United States)
1994-12-31
Multigrid solution technique to solve a material nonlinear problem in a visual programming environment using the finite element method is discussed. The nonlinear equation of equilibrium is linearized to incremental form using Newton-Rapson technique, then multigrid solution technique is used to solve linear equations at each Newton-Rapson step. In the process, adaptive mesh refinement, which is based on the bisection of a pair of triangles, is used to form grid hierarchy for multigrid iteration. The solution process is implemented in a visual programming environment with distributed computing capability, which enables more intuitive understanding of solution process, and more effective use of resources.
Geometric and engineering drawing
Morling, K
2010-01-01
The new edition of this successful text describes all the geometric instructions and engineering drawing information that are likely to be needed by anyone preparing or interpreting drawings or designs with plenty of exercises to practice these principles.
Differential geometric structures
Poor, Walter A
2007-01-01
This introductory text defines geometric structure by specifying parallel transport in an appropriate fiber bundle and focusing on simplest cases of linear parallel transport in a vector bundle. 1981 edition.
Bledsoe, Gloria J
1987-01-01
The game of "Guess What" is described as a stimulating vehicle for students to consider the unifying or distinguishing features of geometric figures. Teaching suggestions as well as the gameboard are provided. (MNS)
Hinz, Denis F
2014-01-01
This article is a translation of Michael Sadowsky's original paper "Ein elementarer Beweis f\\"ur die Existenz eines abwickelbaren M\\"obiusschen Bandes und die Zur\\"uckf\\"uhrung des geometrischen Problems auf ein Variationsproblem." which appeared in Sitzungsberichte der Preussischen Akademie der Wissenschaften, physikalisch-mathematische Klasse, 17. Juli 1930, Mitteilung vom 26. Juni, 412-415. Published on September 12, 1930.
Saturation and geometrical scaling
Praszalowicz, Michal
2016-01-01
We discuss emergence of geometrical scaling as a consequence of the nonlinear evolution equations of QCD, which generate a new dynamical scale, known as the saturation momentum: Qs. In the kinematical region where no other energy scales exist, particle spectra exhibit geometrical scaling (GS), i.e. they depend on the ratio pT=Qs, and the energy dependence enters solely through the energy dependence of the saturation momentum. We confront the hypothesis of GS in different systems with experimental data.
Geometrical method of decoupling
Baumgarten, C.
2012-12-01
The computation of tunes and matched beam distributions are essential steps in the analysis of circular accelerators. If certain symmetries—like midplane symmetry—are present, then it is possible to treat the betatron motion in the horizontal, the vertical plane, and (under certain circumstances) the longitudinal motion separately using the well-known Courant-Snyder theory, or to apply transformations that have been described previously as, for instance, the method of Teng and Edwards. In a preceding paper, it has been shown that this method requires a modification for the treatment of isochronous cyclotrons with non-negligible space charge forces. Unfortunately, the modification was numerically not as stable as desired and it was still unclear, if the extension would work for all conceivable cases. Hence, a systematic derivation of a more general treatment seemed advisable. In a second paper, the author suggested the use of real Dirac matrices as basic tools for coupled linear optics and gave a straightforward recipe to decouple positive definite Hamiltonians with imaginary eigenvalues. In this article this method is generalized and simplified in order to formulate a straightforward method to decouple Hamiltonian matrices with eigenvalues on the real and the imaginary axis. The decoupling of symplectic matrices which are exponentials of such Hamiltonian matrices can be deduced from this in a few steps. It is shown that this algebraic decoupling is closely related to a geometric “decoupling” by the orthogonalization of the vectors E→, B→, and P→, which were introduced with the so-called “electromechanical equivalence.” A mathematical analysis of the problem can be traced down to the task of finding a structure-preserving block diagonalization of symplectic or Hamiltonian matrices. Structure preservation means in this context that the (sequence of) transformations must be symplectic and hence canonical. When used iteratively, the decoupling
Creativity and Motivation for Geometric Tasks Designing in Education
Rumanová, Lucia; Smiešková, Edita
2015-01-01
In this paper we focus on creativity needed for geometric tasks designing, visualization of geometric problems and use of ICT. We present some examples of various problems related to tessellations. Altogether 21 students--pre-service teachers participated in our activity within a geometry course at CPU in Nitra, Slovakia. Our attempt was to…
Mixed-integer programming methods for transportation and power generation problems
Damci Kurt, Pelin
This dissertation conducts theoretical and computational research to solve challenging problems in application areas such as supply chain and power systems. The first part of the dissertation studies a transportation problem with market choice (TPMC) which is a variant of the classical transportation problem in which suppliers with limited capacities have a choice of which demands (markets) to satisfy. We show that TPMC is strongly NP-complete. We consider a version of the problem with a service level constraint on the maximum number of markets that can be rejected and show that if the original problem is polynomial, its cardinality-constrained version is also polynomial. We propose valid inequalities for mixed-integer cover and knapsack sets with variable upper bound constraints, which appear as substructures of TPMC and use them in a branch-and-cut algorithm to solve this problem. The second part of this dissertation studies a unit commitment (UC) problem in which the goal is to minimize the operational cost of power generators over a time period subject to physical constraints while satisfying demand. We provide several exponential classes of multi-period ramping and multi-period variable upper bound inequalities. We prove the strength of these inequalities and describe polynomial-time separation algorithms. Computational results show the effectiveness of the proposed inequalities when used as cuts in a branch-and-cut algorithm to solve the UC problem. The last part of this dissertation investigates the effects of uncertain wind power on the UC problem. A two-stage robust model and a three-stage stochastic program are compared.
The solution of the optimization problem of small energy complexes using linear programming methods
Ivanin, O. A.; Director, L. B.
2016-11-01
Linear programming methods were used for solving the optimization problem of schemes and operation modes of distributed generation energy complexes. Applicability conditions of simplex method, applied to energy complexes, including installations of renewable energy (solar, wind), diesel-generators and energy storage, considered. The analysis of decomposition algorithms for various schemes of energy complexes was made. The results of optimization calculations for energy complexes, operated autonomously and as a part of distribution grid, are presented.
Modeling Dynamic Programming Problems over Sequences and Trees with Inverse Coupled Rewrite Systems
2014-01-01
International audience; Dynamic programming is a classical algorithmic paradigm, which often allows the evaluation of a search space of exponential size in polynomial time. Recursive problem decomposition, tabulation of intermediate results for re-use, and Bellman's Principle of Optimality are its well-understood ingredients. However, algorithms often lack abstraction and are difficult to implement, tedious to debug, and delicate to modify. The present article proposes a generic framework for...
Introduction of problem-based learning in undergraduate dentistry program in Nepal
Rimal, Jyotsna; Paudel, Bishnu Hari; Shrestha, Ashish
2015-01-01
Context: Problem-based learning (PBL) is a methodology widely used in medical education and is growing in dental education. Initiation of new ideas and teaching methods requires a change in perception from faculty and institute management. Student-centered education is a need of the day and PBL provides the best outlet to it. Aim: To introduce PBL, assess feasibility and challenges in undergraduate dentistry program and evaluate the impact on their learning. Settings and Design: PBL was used ...
Feng, Ruibin; Leung, Chi-Sing; Constantinides, Anthony G; Zeng, Wen-Jun
2016-07-27
The major limitation of the Lagrange programming neural network (LPNN) approach is that the objective function and the constraints should be twice differentiable. Since sparse approximation involves nondifferentiable functions, the original LPNN approach is not suitable for recovering sparse signals. This paper proposes a new formulation of the LPNN approach based on the concept of the locally competitive algorithm (LCA). Unlike the classical LCA approach which is able to solve unconstrained optimization problems only, the proposed LPNN approach is able to solve the constrained optimization problems. Two problems in sparse approximation are considered. They are basis pursuit (BP) and constrained BP denoise (CBPDN). We propose two LPNN models, namely, BP-LPNN and CBPDN-LPNN, to solve these two problems. For these two models, we show that the equilibrium points of the models are the optimal solutions of the two problems, and that the optimal solutions of the two problems are the equilibrium points of the two models. Besides, the equilibrium points are stable. Simulations are carried out to verify the effectiveness of these two LPNN models.
Goal-programming model of the stochastic vehicle-routing problem
Energy Technology Data Exchange (ETDEWEB)
Zare-Mehrjerdi, Y.
1986-01-01
This research proposes a Goal Programming (GP) model of the Stochastic Vehicle Routing Problem (SVRP). The SVRP examined considers the multiple-vehicle, single-depot-node routing problem in which customer demand and travel and unload times are random variables having known distribution functions. The problem formulation of the SVRP is divided into two major stages which are referred to as Route Construction Stage (RCS) and Route Improvement Stage (RIS). The RCS of the SVRP is required in order to partition a set of stations into feasible sets of routes, one for each vehicle, using an appropriate heuristic approach. The RIS of the problem is required in order to sequence the stations on each vehicle route to meet the customer's and decision maker's requirements by applying a GP method. Two problems discuss the GP formulation of the RIS, which is used for improving the arrangement of stations on each vehicle route based on the customer's and decision maker's criteria. The formulation of the RCS of the problem is divided into two sections according to the type of criteria that is to be minimized. A substantial improvement in the results of the SVRP can be obtained by integrating the customer's and decision maker's requirements with the SVRP in order to determine the final arrangement of stations for each vehicle route.
Pol, Henk J.; Harskamp, Egbert G.; Suhre, Cor J. M.; Goedhart, Martin J.
2008-01-01
Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing
Pol, Henk J.; Harskamp, Egbert G.; Suhre, Cor J. M.; Goedhart, Martin J.
Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing
Institute of Scientific and Technical Information of China (English)
ZhuDetong
2004-01-01
This paper proposes a nonmonotonic backtracking trust region algorithm via bilevel linear programming for solving the general multicommodity minimal cost flow problems. Using the duality theory of the linear programming and convex theory, the generalized directional derivative of the general multicommodity minimal cost flow problems is derived. The global convergence and superlinear convergence rate of the proposed algorithm are established under some mild conditions.
Pol, Henk J.; Harskamp, Egbert G.; Suhre, Cor J. M.; Goedhart, Martin J.
2008-01-01
Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing their strategic knowledge in combination with…
Pol, Henk J.; Harskamp, Egbert G.; Suhre, Cor J. M.; Goedhart, Martin J.
2008-01-01
Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing their strategic knowledge in combination with…
A Toolbox for Geometric Grain Boundary Characterization
Glowinski, Krzysztof; Morawiec, Adam
Properties of polycrystalline materials are affected by grain boundary networks. The most basic aspect of boundary analysis is boundary geometry. This paper describes a package of computer programs for geometric boundary characterization based on macroscopic boundary parameters. The program allows for determination whether a boundary can be classified as near-tilt, -twist, -symmetric et cetera. Since calculations on experimental, i.e., error affected data are assumed, the program also provides distances to the nearest geometrically characteristic boundaries. The software has a number of other functions helpful in grain boundary analysis. One of them is the determination of planes of all characteristic boundaries for a given misorientation. The resulting diagrams of geometrically characteristic boundaries can be linked to experimentally determined grain boundary distributions. In computations, all symmetrically equivalent representations of boundaries are taken into account. Cubic and hexagonal holohedral crystal symmetries are allowed.
Directory of Open Access Journals (Sweden)
Mitre-Hernández Hugo A.
2014-04-01
Full Text Available Software measurement is widely recognized as an essential part of understanding, controlling, monitoring, predicting, and evaluating software development and maintenance projects. Both, software process improvement (SPI and software measurement literature include many case studies of successful companies and descriptions of their measurement programs. However, there are still concerns on how to design efficient strategic measurement programs. These concerns include the lack of involvement of the SEO’s personnel, bad alignment with its strategy and improvement initiative, difficulty to justify the utility of using standards or improvement initiatives, etc. All of the former results in inadequate measurement programs that often lead to poor decisions and economic loss. This paper describes a pilot study to observe and analyze the operation of measurement teams when using measurement methods such as Balanced Objective-Quantifiers Method (BOQM, Practical Software Measurement (PSM and Balanced Scorecard and Goal-Driven Measurement (BSC&GQ[I]M to design a strategic measurement program. From the results of the study, we gained some insight on common difficulties and problems, which are useful to consider when designing of strategic measurement programs. This paper describes an important milestone in achieving our main research goal, evaluate and find suggestions to design a strategic measurement program aligned correctly with the strategic goals, for effective decision making at all organization levels and justify the utilities or benefits of integrating improvement initiatives.
Field guide to geometrical optics
Greivenkamp, John E
2004-01-01
This Field Guide derives from the treatment of geometrical optics that has evolved from both the undergraduate and graduate programs at the Optical Sciences Center at the University of Arizona. The development is both rigorous and complete, and it features a consistent notation and sign convention. This volume covers Gaussian imagery, paraxial optics, first-order optical system design, system examples, illumination, chromatic effects, and an introduction to aberrations. The appendices provide supplemental material on radiometry and photometry, the human eye, and several other topics.
A Mixed Integer Programming Poultry Feed Ration Optimisation Problem Using the Bat Algorithm
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Godfrey Chagwiza
2016-01-01
Full Text Available In this paper, a feed ration problem is presented as a mixed integer programming problem. An attempt to find the optimal quantities of Moringa oleifera inclusion into the poultry feed ration was done and the problem was solved using the Bat algorithm and the Cplex solver. The study used findings of previous research to investigate the effects of Moringa oleifera inclusion in poultry feed ration. The results show that the farmer is likely to gain US$0.89 more if Moringa oleifera is included in the feed ration. Results also show superiority of the Bat algorithm in terms of execution time and number of iterations required to find the optimum solution as compared with the results obtained by the Cplex solver. Results revealed that there is a significant economic benefit of Moringa oleifera inclusion into the poultry feed ration.
Fuzzy linear fractional bi-level multi-objective programming problems
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nemat safaei
2012-08-01
Full Text Available The Kuhn-Tuker condition has become nowadays an important tool in the hands of investigation for checking the optimality in optimization literature. In the present paper with use of a Taylor series and Kuhn-Tucker conditions approach, we solve a fuzzy linear fractional bilevel multi-objective programming (FLFBL-MOP problem. The Taylor series is an expansion of a series that represents a function. In the proposed approach, membership functions associated with each level(s ofthe objective(s of FLFBL-MOP problems are transformed and unied by using a Taylor series approach. By using the Kuhn-Tucker conditions, the problem is reduced to a single objective and nally, numericalexample is given to illustrates the efficiency and superiority of the proposed approach.
A simulation based research on chance constrained programming in robust facility location problem
Kaijun, Leng; Wen, Shi; Guanghua, Song; Lin, Pan
2017-03-01
Since facility location decisions problem include long-term character and potential parameter variations, it is important to consider uncertainty in its modeling. This paper examines robust facility location problem considering supply uncertainty, in which we assume the supply of the facility in the actual operation is not equal to the supply initially established, the supply is subject to random fluctuation. The chance constraints are introduced when formulating the robust facility location model to make sure the system operate properly with a certain probability while the supply fluctuates. The chance constraints are approximated safely by using Hoeffding's inequality and the problem is transformed to a general deterministic linear programming. Furthermore, how the facility location cost change with confidence level is investigated through a numerical example. The sensitivity analysis is conducted for important parameters of the model and we get the main factors that affect the facility location cost.
Techniques that strive to combat the influence of degeneracy in linear programming problems
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J.H. Nel
2003-12-01
Full Text Available Degeneracy can cause enormous problems when solving large scale linear programming problems. This is not only because there is a possibility that the problem can cycle, but also because a large number of iterations can be executed that do not improve the objective. In this article a procedure which utilises derived reduced costs is discussed. The derived reduced cost of a non- basic variable is defined in such a way that it makes the introduction to the non-basic variable into the basis unattractive if such a decision fails to improve the objective. The procedure deliberately strives to combat degeneracy using derived reduced costs, but it also utilises the advantageous properties of the classical gradient methods.
Zenith Pass Problem of Inter-satellite Linkage Antenna Based on Program Guidance Method
Institute of Scientific and Technical Information of China (English)
Zhai Kun; Yang Di
2008-01-01
While adopting an elevation-over-azimuth architecture by an inter-satellite linkage antenna of a user satellite, a zenith pass problem always occurs when the antenna is tracing the tracking and data relay satellite (TDRS). This paper deals with this problem by way of,firstly, introducing movement laws of the inter-satellite linkage to predict the movement of the user satellite antenna followed by analyzing the potential pass moment and the actual one of the zenith pass in detail. A number of specific orbit altitudes for the user satellite that can remove the blindness zone are obtained. Finally, on the base of the predicted results from the movement laws of the inter-satellite linkage, the zenith pass tracing strategies for the user satellite antenna are designed under the program guidance using a trajectory preprocessor. Simulations have confirmed the reasonability and feasibility of the strategies in dealing with the zenith pass problem.
An integer programming model for gate assignment problem at airline terminals
Chun, Chong Kok; Nordin, Syarifah Zyurina
2015-05-01
In this paper, we concentrate on a gate assignment problem (GAP) at the airlines terminal. Our problem is to assign an arrival plane to a suitable gate. There are two considerations needed to take. One of its is passenger walking distance from arrival gate to departure gate while another consideration is the transport baggage distance from one gate to another. Our objective is to minimize the total distance between the gates that related to assign the arrival plane to the suitable gates. An integer linear programming (ILP) model is proposed to solve this gate assignment problem. We also conduct a computational experiment using CPLEX 12.1 solver in AIMMS 3.10 software to analyze the performance of the model. Results of the computational experiments are presented. The efficiency of flights assignment is depends on the ratio of the weight for both total passenger traveling distances and total baggage transport distances.
Directory of Open Access Journals (Sweden)
Sunxin Wang
2014-01-01
Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.
Directory of Open Access Journals (Sweden)
Yekini Shehu
2010-01-01
real Banach space which is also uniformly smooth using the properties of generalized f-projection operator. Using this result, we discuss strong convergence theorem concerning general H-monotone mappings and system of generalized mixed equilibrium problems in Banach spaces. Our results extend many known recent results in the literature.
Clark, S.G.; Rutherford, M.B.; Auer, M.R.; Cherney, D.N.; Wallace, R.L.; Mattson, D.J.; Clark, D.A.; Foote, L.; Krogman, N.; Wilshusen, P.; Steelman, T.
2011-01-01
Environmental studies and environmental sciences programs in American and Canadian colleges and universities seek to ameliorate environmental problems through empirical enquiry and analytic judgment. In a companion article (Part 1) we describe the environmental program movement (EPM) and discuss factors that have hindered its performance. Here, we complete our analysis by proposing strategies for improvement. We recommend that environmental programs re-organize around three principles. First, adopt as an overriding goal the concept of human dignity-defined as freedom and social justice in healthy, sustainable environments. This clear higher-order goal captures the human and environmental aspirations of the EPM and would provide a more coherent direction for the efforts of diverse participants. Second, employ an explicit, genuinely interdisciplinary analytical framework that facilitates the use of multiple methods to investigate and address environmental and social problems in context. Third, develop educational programs and applied experiences that provide students with the technical knowledge, powers of observation, critical thinking skills and management acumen required for them to become effective professionals and leaders. Organizing around these three principles would build unity in the EPM while at the same time capitalizing on the strengths of the many disciplines and diverse local conditions involved. ?? 2011 Springer Science+Business Media, LLC.
Solving seismological problems using SGRAPH program: I-source parameters and hypocentral location
Abdelwahed, Mohamed F.
2012-09-01
SGRAPH program [1] is considered one of the seismological programs that maintain seismic data. SGRAPH is considered unique for being able to read a wide range of data formats and manipulate complementary tools in different seismological subjects in a stand-alone Windows-based application. SGRAPH efficiently performs the basic waveform analysis and solves advanced seismological problems. The graphical user interface (GUI) utilities and the Windows facilities such as, dialog boxes, menus, and toolbars simplified the user interaction with data. SGRAPH supported the common data formats like, SAC, SEED, GSE, ASCII, and Nanometrics Y-format, and others. It provides the facilities to solve many seismological problems with the built-in inversion and modeling tools. In this paper, I discuss some of the inversion tools built-in SGRAPH related to source parameters and hypocentral location estimation. Firstly, a description of the SGRAPH program is given discussing some of its features. Secondly, the inversion tools are applied to some selected events of the Dahshour earthquakes as an example of estimating the spectral and source parameters of local earthquakes. In addition, the hypocentral location of these events are estimated using the Hypoinverse 2000 program [2] operated by SGRAPH.
An optimal approach for the critical node problem using semidefinite programming
Jiang, Cheng; Liu, Zhonghua; Wang, Juyun; Yu, Hua; Guo, Xiaoling
2017-04-01
Detecting critical nodes in complex networks (CNP) has great theoretical and practical significance in many disciplines. The existing formulations for CNP are mostly, as we know, based on the integer linear programming model. However, we observed that, these formulations only considered the sizes but neglected the cohesiveness properties of the connected components in the induced network. To solve the problem and improve the performance of CNP solutions, we construct a novel nonconvex quadratically constrained quadratic programming (QCQP) model and derive its approximation solutions via semidefinite programming (SDP) technique and heuristic algorithms. Various types of synthesized and real-world networks, in the context of different connectivity patterns, are used to validate and verify the effectiveness of the proposed model and algorithm. Experimental results show that our method improved the state of the art of the CNP.
Fuzzy Programming With Quadratic Membership Functions For Multi-objective Transportation Problem
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Satyanarayana Murthy Akkapeddi
2015-08-01
Full Text Available In the present paper, a fuzzy programming model with quadratic membership functions has been developed for the solution of a Multi-Objective Transportation problem. In literature, several fuzzy programming approaches exist with various types of membership functions such as linear, exponential, hyperbolic etc. These membership functions are defined, by taking the lower and upper values of the objective functions into account. In some cases, these methods fail to obtain an integer compromise optimal solution. In the present method, two coefficients of the quadratic membership functions are determined by the lower and upper values of the objective functions. The other coefficient is taken as a variable in the fuzzy programming approach. This means that the membership curve is fixed at the two end points and set free in between. Application of the method on numerical examples proved that the approach could generate integer compromise optimal solutions.
Assessment of the NASA Space Shuttle Program's Problem Reporting and Corrective Action System
Korsmeryer, D. J.; Schreiner, J. A.; Norvig, Peter (Technical Monitor)
2001-01-01
This paper documents the general findings and recommendations of the Design for Safety Programs Study of the Space Shuttle Programs (SSP) Problem Reporting and Corrective Action (PRACA) System. The goals of this Study were: to evaluate and quantify the technical aspects of the SSP's PRACA systems, and to recommend enhancements addressing specific deficiencies in preparation for future system upgrades. The Study determined that the extant SSP PRACA systems accomplished a project level support capability through the use of a large pool of domain experts and a variety of distributed formal and informal database systems. This operational model is vulnerable to staff turnover and loss of the vast corporate knowledge that is not currently being captured by the PRACA system. A need for a Program-level PRACA system providing improved insight, unification, knowledge capture, and collaborative tools was defined in this study.
2001-01-01
The primary purpose of this thesis is to investigate the problems of retaining qualified personnel in the Program Manager for Chemical Demilitarization organization through the end date of the program. To accomplish this the Program Manager for Chemical Demilitarization organization was analyzed from an open system prospective to identify the elements within the organization, and in the larger organizational environment, that are expected to contribute to the retention problem. In addition th...
Geometric systematic prostate biopsy.
Chang, Doyoung; Chong, Xue; Kim, Chunwoo; Jun, Changhan; Petrisor, Doru; Han, Misop; Stoianovici, Dan
2017-04-01
The common sextant prostate biopsy schema lacks a three-dimensional (3D) geometric definition. The study objective was to determine the influence of the geometric distribution of the cores on the detection probability of prostate cancer (PCa). The detection probability of significant (>0.5 cm(3)) and insignificant (geometric distribution of the cores was optimized to maximize the probability of detecting significant cancer for various prostate sizes (20-100cm(3)), number of biopsy cores (6-40 cores) and biopsy core lengths (14-40 mm) for transrectal and transperineal biopsies. The detection of significant cancer can be improved by geometric optimization. With the current sextant biopsy, up to 20% of tumors may be missed at biopsy in a 20 cm(3) prostate due to the schema. Higher number and longer biopsy cores are required to sample with an equal detection probability in larger prostates. Higher number of cores increases both significant and insignificant tumor detection probability, but predominantly increases the detection of insignificant tumors. The study demonstrates mathematically that the geometric biopsy schema plays an important clinical role, and that increasing the number of biopsy cores is not necessarily helpful.
Wu, Z; Zhang, Y
2008-01-01
The double digestion problem for DNA restriction mapping has been proved to be NP-complete and intractable if the numbers of the DNA fragments become large. Several approaches to the problem have been tested and proved to be effective only for small problems. In this paper, we formulate the problem as a mixed-integer linear program (MIP) by following (Waterman, 1995) in a slightly different form. With this formulation and using state-of-the-art integer programming techniques, we can solve randomly generated problems whose search space sizes are many-magnitude larger than previously reported testing sizes.
Geometric Rationalization for Freeform Architecture
Jiang, Caigui
2016-06-20
The emergence of freeform architecture provides interesting geometric challenges with regards to the design and manufacturing of large-scale structures. To design these architectural structures, we have to consider two types of constraints. First, aesthetic constraints are important because the buildings have to be visually impressive. Sec- ond, functional constraints are important for the performance of a building and its e cient construction. This thesis contributes to the area of architectural geometry. Specifically, we are interested in the geometric rationalization of freeform architec- ture with the goal of combining aesthetic and functional constraints and construction requirements. Aesthetic requirements typically come from designers and architects. To obtain visually pleasing structures, they favor smoothness of the building shape, but also smoothness of the visible patterns on the surface. Functional requirements typically come from the engineers involved in the construction process. For exam- ple, covering freeform structures using planar panels is much cheaper than using non-planar ones. Further, constructed buildings have to be stable and should not collapse. In this thesis, we explore the geometric rationalization of freeform archi- tecture using four specific example problems inspired by real life applications. We achieve our results by developing optimization algorithms and a theoretical study of the underlying geometrical structure of the problems. The four example problems are the following: (1) The design of shading and lighting systems which are torsion-free structures with planar beams based on quad meshes. They satisfy the functionality requirements of preventing light from going inside a building as shad- ing systems or reflecting light into a building as lighting systems. (2) The Design of freeform honeycomb structures that are constructed based on hex-dominant meshes with a planar beam mounted along each edge. The beams intersect without
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Yen-Liang Pan
2013-01-01
Full Text Available Deadlock prevention policies are used to solve the deadlock problems of FMSs. It is well known that the theory of regions is the efficient method for obtaining optimal (i.e., maximally permissive controllers. All legal and live maximal behaviors of Petri net models can be preserved by using marking/transition-separation instances (MTSIs or event-state-separation-problem (ESSP methods. However, they encountered great difficulties in solving all sets of inequalities that is an extremely time consuming problem. Moreover, the number of linear programming problems (LPPs of legal markings is also exponential with net size when a plant net grows exponentially. This paper proposes a novel methodology to reduce the number of MTSIs/ESSPs and LPPs. In this paper, we used the well-known reduction approach Murata (1989 to simply the construct of system such that the problem of LPPs can then be reduced. Additionally, critical ones of crucial marking/transition-separation instances (COCMTSI are developed and used in our deadlock prevention policy that allows designers to employ few MTSIs to deal with deadlocks. Experimental results indicate that the computational cost can be reduced. To our knowledge, this deadlock prevention policy is the most efficient policy to obtain maximal permissive behavior of Petri net models than past approaches.
The product contains user-friendly computer programs for solving sampling and related statistical problems. All have been updated as well and more programs have been added. Specific, detailed written instructions and examples built into the programs are provided so that the user ...
Li, Yanning
2013-10-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
A Fuzzy Goal Programming for a Multi-Depot Distribution Problem
Nunkaew, Wuttinan; Phruksaphanrat, Busaba
2010-10-01
A fuzzy goal programming model for solving a Multi-Depot Distribution Problem (MDDP) is proposed in this research. This effective proposed model is applied for solving in the first step of Assignment First-Routing Second (AFRS) approach. Practically, a basic transportation model is firstly chosen to solve this kind of problem in the assignment step. After that the Vehicle Routing Problem (VRP) model is used to compute the delivery cost in the routing step. However, in the basic transportation model, only depot to customer relationship is concerned. In addition, the consideration of customer to customer relationship should also be considered since this relationship exists in the routing step. Both considerations of relationships are solved using Preemptive Fuzzy Goal Programming (P-FGP). The first fuzzy goal is set by a total transportation cost and the second fuzzy goal is set by a satisfactory level of the overall independence value. A case study is used for describing the effectiveness of the proposed model. Results from the proposed model are compared with the basic transportation model that has previously been used in this company. The proposed model can reduce the actual delivery cost in the routing step owing to the better result in the assignment step. Defining fuzzy goals by membership functions are more realistic than crisps. Furthermore, flexibility to adjust goals and an acceptable satisfactory level for decision maker can also be increased and the optimal solution can be obtained.
Park, Y. C.; Chang, M. H.; Lee, T.-Y.
2007-06-01
A deterministic global optimization method that is applicable to general nonlinear programming problems composed of twice-differentiable objective and constraint functions is proposed. The method hybridizes the branch-and-bound algorithm and a convex cut function (CCF). For a given subregion, the difference of a convex underestimator that does not need an iterative local optimizer to determine the lower bound of the objective function is generated. If the obtained lower bound is located in an infeasible region, then the CCF is generated for constraints to cut this region. The cutting region generated by the CCF forms a hyperellipsoid and serves as the basis of a discarding rule for the selected subregion. However, the convergence rate decreases as the number of cutting regions increases. To accelerate the convergence rate, an inclusion relation between two hyperellipsoids should be applied in order to reduce the number of cutting regions. It is shown that the two-hyperellipsoid inclusion relation is determined by maximizing a quadratic function over a sphere, which is a special case of a trust region subproblem. The proposed method is applied to twelve nonlinear programming test problems and five engineering design problems. Numerical results show that the proposed method converges in a finite calculation time and produces accurate solutions.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.
Geometrical method of decoupling
Directory of Open Access Journals (Sweden)
C. Baumgarten
2012-12-01
Full Text Available The computation of tunes and matched beam distributions are essential steps in the analysis of circular accelerators. If certain symmetries—like midplane symmetry—are present, then it is possible to treat the betatron motion in the horizontal, the vertical plane, and (under certain circumstances the longitudinal motion separately using the well-known Courant-Snyder theory, or to apply transformations that have been described previously as, for instance, the method of Teng and Edwards. In a preceding paper, it has been shown that this method requires a modification for the treatment of isochronous cyclotrons with non-negligible space charge forces. Unfortunately, the modification was numerically not as stable as desired and it was still unclear, if the extension would work for all conceivable cases. Hence, a systematic derivation of a more general treatment seemed advisable. In a second paper, the author suggested the use of real Dirac matrices as basic tools for coupled linear optics and gave a straightforward recipe to decouple positive definite Hamiltonians with imaginary eigenvalues. In this article this method is generalized and simplified in order to formulate a straightforward method to decouple Hamiltonian matrices with eigenvalues on the real and the imaginary axis. The decoupling of symplectic matrices which are exponentials of such Hamiltonian matrices can be deduced from this in a few steps. It is shown that this algebraic decoupling is closely related to a geometric “decoupling” by the orthogonalization of the vectors E[over →], B[over →], and P[over →], which were introduced with the so-called “electromechanical equivalence.” A mathematical analysis of the problem can be traced down to the task of finding a structure-preserving block diagonalization of symplectic or Hamiltonian matrices. Structure preservation means in this context that the (sequence of transformations must be symplectic and hence canonical. When
Sabar, Nasser R; Ayob, Masri; Kendall, Graham; Qu, Rong
2015-02-01
Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite.
Graff, Mario; Poli, Riccardo; Flores, Juan J
2013-01-01
Modeling the behavior of algorithms is the realm of evolutionary algorithm theory. From a practitioner's point of view, theory must provide some guidelines regarding which algorithm/parameters to use in order to solve a particular problem. Unfortunately, most theoretical models of evolutionary algorithms are difficult to apply to realistic situations. However, in recent work (Graff and Poli, 2008, 2010), where we developed a method to practically estimate the performance of evolutionary program-induction algorithms (EPAs), we started addressing this issue. The method was quite general; however, it suffered from some limitations: it required the identification of a set of reference problems, it required hand picking a distance measure in each particular domain, and the resulting models were opaque, typically being linear combinations of 100 features or more. In this paper, we propose a significant improvement of this technique that overcomes the three limitations of our previous method. We achieve this through the use of a novel set of features for assessing problem difficulty for EPAs which are very general, essentially based on the notion of finite difference. To show the capabilities or our technique and to compare it with our previous performance models, we create models for the same two important classes of problems-symbolic regression on rational functions and Boolean function induction-used in our previous work. We model a variety of EPAs. The comparison showed that for the majority of the algorithms and problem classes, the new method produced much simpler and more accurate models than before. To further illustrate the practicality of the technique and its generality (beyond EPAs), we have also used it to predict the performance of both autoregressive models and EPAs on the problem of wind speed forecasting, obtaining simpler and more accurate models that outperform in all cases our previous performance models.
An Integer Linear Programming Solution to the Telescope Network Scheduling Problem
Lampoudi, Sotiria; Eastman, Jason
2015-01-01
Telescope networks are gaining traction due to their promise of higher resource utilization than single telescopes and as enablers of novel astronomical observation modes. However, as telescope network sizes increase, the possibility of scheduling them completely or even semi-manually disappears. In an earlier paper, a step towards software telescope scheduling was made with the specification of the Reservation formalism, through the use of which astronomers can express their complex observation needs and preferences. In this paper we build on that work. We present a solution to the discretized version of the problem of scheduling a telescope network. We derive a solvable integer linear programming (ILP) model based on the Reservation formalism. We show computational results verifying its correctness, and confirm that our Gurobi-based implementation can address problems of realistic size. Finally, we extend the ILP model to also handle the novel observation requests that can be specified using the more advanc...
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
Directory of Open Access Journals (Sweden)
Zongyuan Huang
2010-01-01
Full Text Available This paper is concerned with a kind of corporate international optimal portfolio and consumption choice problems, in which the investor can invest her or his wealth either in a domestic bond (bank account or in an oversea real project with production. The bank pays a lower interest rate for deposit and takes a higher rate for any loan. First, we show that Bellman's dynamic programming principle still holds in our setting; second, in terms of the foregoing principle, we obtain the investor's optimal portfolio proportion for a general maximizing expected utility problem and give the corresponding economic analysis; third, for the special but nontrivial Constant Relative Risk Aversion (CRRA case, we get the investors optimal investment and consumption solution; last but not least, we give some numerical simulation results to illustrate the influence of volatility parameters on the optimal investment strategy.
Institute of Scientific and Technical Information of China (English)
周南; 郭光靖; 唐先亮; 陈强
2012-01-01
基于MATLAB编写的程序能够对水稻种子图像进行分析,提取出种子的几何特征。将拍摄的水稻种子图像,读入程序以后,进行类型转换、顶帽变换、灰度开运算等方法对图像进行预处理,接着用最大类间方差法分割图像、标注连通区、画出最小外接矩、提取几何特征、输出数据等。实现了数据自动化检测统计,为自动化考种、品质分析等提供参考,丰富了国内相关领域的研究内容。%The MATLAB-based GUI（Graphical User Interface） program can be used to analysis the picture of rice seeds to achieve geometrical characteristics.After the readin of the digital picture,the program preprocess the photo with type conversion,hat transforming,gray open operation,and then split it with OTSU method,line the minimum external moment,collect geometrical characteristics,display data,etc.The program automaticly fulfill the task of collection data and,in this way,the inspection of rice seeds,qualitative analysis,correlational researches inland and so forth can get services.
PREFACE: Geometrically frustrated magnetism Geometrically frustrated magnetism
Gardner, Jason S.
2011-04-01
Frustrated magnetism is an exciting and diverse field in condensed matter physics that has grown tremendously over the past 20 years. This special issue aims to capture some of that excitement in the field of geometrically frustrated magnets and is inspired by the 2010 Highly Frustrated Magnetism (HFM 2010) meeting in Baltimore, MD, USA. Geometric frustration is a broad phenomenon that results from an intrinsic incompatibility between some fundamental interactions and the underlying lattice geometry based on triangles and tetrahedra. Most studies have centred around the kagomé and pyrochlore based magnets but recent work has looked at other structures including the delafossite, langasites, hyper-kagomé, garnets and Laves phase materials to name a few. Personally, I hope this issue serves as a great reference to scientist both new and old to this field, and that we all continue to have fun in this very frustrated playground. Finally, I want to thank the HFM 2010 organizers and all the sponsors whose contributions were an essential part of the success of the meeting in Baltimore. Geometrically frustrated magnetism contents Spangolite: an s = 1/2 maple leaf lattice antiferromagnet? T Fennell, J O Piatek, R A Stephenson, G J Nilsen and H M Rønnow Two-dimensional magnetism and spin-size effect in the S = 1 triangular antiferromagnet NiGa2S4 Yusuke Nambu and Satoru Nakatsuji Short range ordering in the modified honeycomb lattice compound SrHo2O4 S Ghosh, H D Zhou, L Balicas, S Hill, J S Gardner, Y Qi and C R Wiebe Heavy fermion compounds on the geometrically frustrated Shastry-Sutherland lattice M S Kim and M C Aronson A neutron polarization analysis study of moment correlations in (Dy0.4Y0.6)T2 (T = Mn, Al) J R Stewart, J M Hillier, P Manuel and R Cywinski Elemental analysis and magnetism of hydronium jarosites—model kagome antiferromagnets and topological spin glasses A S Wills and W G Bisson The Herbertsmithite Hamiltonian: μSR measurements on single crystals
Inamoto, Tsutomu; Tamaki, Hisashi; Murao, Hajime
In this paper, we present a modified dynamic programming (DP) method. The method is basically the same as the value iteration method (VI), a representative DP method, except the preprocess of a system's state transition model for reducing its complexity, and is called the dynamic programming on reduced models (DPRM). That reduction is achieved by imaginarily considering causes of the probabilistic behavior of a system, and then cutting off some causes with low occurring probabilities. In computational illustrations, VI, DPRM, and the real-time Q-learning method (RTQ) are applied to elevator operation problems, which can be modeled by using Markov decision processes. The results show that DPRM can compute quasi-optimal value functions which bring more effective allocations of elevators than value functions by RTQ in less computational times than VI. This characteristic is notable when the traffic pattern is complicated.
Kelle, Pido I.; Ratterman, Christian; Gibbs, Cecil
2009-01-01
This slide presentation reviews the Constellation Program Problem Reporting, Analysis and Corrective Action Process and System (Cx PRACA). The goal of the Cx PRACA is to incorporate Lessons learned from the Shuttle, ISS, and Orbiter programs by creating a single tool for managing the PRACA process, that clearly defines the scope of PRACA applicability and what must be reported, and defines the ownership and responsibility for managing the PRACA process including disposition approval authority. CxP PRACA is a process, supported by a single information gathering data module which will be integrated with a single CxP Information System, providing interoperability, import and export capability making the CxP PRACA a more effective and user friendly technical and management tool.
Minimax fractional programming problem involving nonsmooth generalized α-univex functions
Directory of Open Access Journals (Sweden)
Anurag JAYSWAL
2013-01-01
Full Text Available In this paper, we introduce a new class of generalized α-univex functions where the involved functions are locally Lipschitz. We extend the concept of α-type I invex [S. K. Mishra, J. S. Rautela, On nondifferentiable minimax fractional programming under generalized α-type I invexity, J. Appl. Math. Comput. 31 (2009 317-334] to α-univexity and an example is provided to show that there exist functions that are α-univex but not α-type I invex. Furthermore, Karush-Kuhn-Tucker-type sufficient optimality conditions and duality results for three different types of dual models are obtained for nondifferentiable minimax fractional programming problem involving generalized α-univex functions. The results in this paper extend some known results in the literature.
Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao
2013-07-01
This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.
On large-scale nonlinear programming techniques for solving optimal control problems
Energy Technology Data Exchange (ETDEWEB)
Faco, J.L.D.
1994-12-31
The formulation of decision problems by Optimal Control Theory allows the consideration of their dynamic structure and parameters estimation. This paper deals with techniques for choosing directions in the iterative solution of discrete-time optimal control problems. A unified formulation incorporates nonlinear performance criteria and dynamic equations, time delays, bounded state and control variables, free planning horizon and variable initial state vector. In general they are characterized by a large number of variables, mostly when arising from discretization of continuous-time optimal control or calculus of variations problems. In a GRG context the staircase structure of the jacobian matrix of the dynamic equations is exploited in the choice of basic and super basic variables and when changes of basis occur along the process. The search directions of the bound constrained nonlinear programming problem in the reduced space of the super basic variables are computed by large-scale NLP techniques. A modified Polak-Ribiere conjugate gradient method and a limited storage quasi-Newton BFGS method are analyzed and modifications to deal with the bounds on the variables are suggested based on projected gradient devices with specific linesearches. Some practical models are presented for electric generation planning and fishery management, and the application of the code GRECO - Gradient REduit pour la Commande Optimale - is discussed.
Havighurst, Sophie S; Wilson, Katherine R; Harley, Ann E; Kehoe, Christiane; Efron, Daryl; Prior, Margot R
2013-04-01
This study evaluated a 6-session group parenting program, Tuning into Kids (TIK), as treatment for young children (aged 4.0-5.11 years) with behavior problems. TIK targets parent emotion socialization (parent emotion awareness, regulation and emotion coaching skills). Fifty-four parents, recruited via a child behavior clinic, were randomized into intervention (TIK) or waitlist (clinical treatment as usual). Parents reported emotion awareness/regulation, emotion coaching, empathy and child behavior (pre-intervention, post-intervention, 6-month follow-up); teachers reported child behavior and observers rated parent-child emotion coaching and child emotion knowledge (pre-intervention, follow-up). Data were analyzed using growth curve modeling and ANCOVA. Parents in both conditions reported less emotional dismissiveness and reduced child behavior problems; in the intervention group, parents also reported greater empathy and had improved observed emotion coaching skills; their children had greater emotion knowledge and reduced teacher-reported behavior problems. TIK appears to be a promising addition to treatment for child behavior problems.
THE PERIODIC CAPACITATED ARC ROUTING PROBLEM LINEAR PROGRAMMING MODEL,METAHEURISTIC AND LOWER BOUNDS
Institute of Scientific and Technical Information of China (English)
Feng CHU; Nacima LABADI; Christian PRINS
2004-01-01
The Periodic Capacitated Arc Routing Problem (PCARP) generalizes the well known NP-hard Capacitated Arc Routing Problem (CARP) by extending the single period to multi-period horizon.The Capacitated Arc Routing Problem (CARP) is defined on an undirected network in which a fleet of identical vehicles is based at a depot node. A subset of edges, called tasks, must be serviced by a vehicle. The CARP consists of determining a set of feasible vehicle trips that minimizes the total cost of traversed edges. The PCARP involves the assignment of tasks to periods and the determination of vehicles trips in each period, to minimize the total cost on the whole horizon. This new problem arises in various real life applications such as waste collection, mail delivery, etc. In this paper, a new linear programming model and preliminary lower bounds based on graph transformation are proposed. A meta-heuristic approach - Scatter Search (SS) is developed for the PCARP and evaluated on a large variety of instances.
Kinsella, John J.
1970-01-01
Discussed are the nature of a mathematical problem, problem solving in the traditional and modern mathematics programs, problem solving and psychology, research related to problem solving, and teaching problem solving in algebra and geometry. (CT)
A NEW SQP-FILTER METHOD FOR SOLVING NONLINEAR PROGRAMMING PROBLEMS
Institute of Scientific and Technical Information of China (English)
Duoquan Li
2006-01-01
In [4],Fletcher and Leyffer present a new method that solves nonlinear programming problems without a penalty function by SQP-Filter algorithm. It has attracted much attention due to its good numerical results. In this paper we propose a new SQP-Filter method which can overcome Maratos effect more effectively. We give stricter acceptant criteria when the iterative points are far from the optimal points and looser ones vice-versa. About this new method,the proof of global convergence is also presented under standard assumptions. Numerical results show that our method is efficient.
A KIND OF FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEMS BASED ON INTERVAL VALUED FUZZY SETS
Institute of Scientific and Technical Information of China (English)
XU Jiuping
2001-01-01
This paper presents a general solution procedure and an interactive fuzzy satisfying method for a kind of fuzzy multi-objective linear programming problems based on interval valued fuzzy sets. Firstly, a fuzzy set of the fuzzy solutions, which can be focused on providing complete information for the final decision, can be obtained by the proposed tolerance analysis of a non-dominated set. Secondly, the satisfying solution for the decisionmaker can be derived from Pareto optimal solutions by updating the current reference membership levels on the basis of the current levels of the membership functions together with the trade-off rates between the membership functions.
Institute of Scientific and Technical Information of China (English)
GAO Ying; RONG Wei-dong
2008-01-01
This paper studies a class of multiobjective generalized fractional programming problems, where the numerators of objective functions are the sum of differentiable function and convex function, while the denominators are the difference of differentiable function and convex function. Under the assumption of Calmness Constraint Qualification the Kuhn-Tucker type necessary conditions for efficient solution are given, and the Kuhn-Tucker type sufficient conditions for efficient solution are presented under the assumptions of (F, α, ρ, d)-V-convexity.Subsequently, the optimality conditions for two kinds of duality models are formulated and duality theorems are proved.
Institute of Scientific and Technical Information of China (English)
LIU Xiao; WANG Cheng-en
2005-01-01
This paper addresses a single item dynamic lot-sizing model with inventory capacity and out-sourcing. The goal is to minimize the total costs of production, setup, inventory holding and out-sourcing. Two versions of an out-sourcing model with time-varying costs are considered: stock out case and conservation case. Zero Inventory Order property has been found and some new properties are obtained in an optimal solution. Dynamic programming algorithms are developed to solve the problem in strongly polynomial time respectively. Furthermore, some numerical results demonstrate that the approach proposed is efficient and applicable.
A quadratic programming problem arising from vector precoding in wireless communications
Müller, R. R.; Guo, D.; Moustakas, A. L.
2008-01-01
A quadratic programming problem is studied in the limit of asymptotically large kernel matrices by means of the replica method. It is found that inverse Wishart kernels are—within the validity range of the replica symmetric solution—asymptotically invariant to Cartesian relaxations. In the context of vector precoding for wireless communication systems with dual antenna arrays, so-called MIMO systems, this implies that adding more transmit antennas cannot reduce the minimum required transmit energy per bit significantly. By contrast, a new convex relaxation is proposed and shown to be a practical and useful method.
Burgess, Claudia R.
2014-01-01
Designed for a broad audience, including educators, camp directors, afterschool coordinators, and preservice teachers, this investigation aims to help individuals experience mathematics in unconventional and exciting ways by engaging them in the physical activity of building geometric shapes using ropes. Through this engagement, the author…
Stuckless, J.S.; VanTrump, G.
1979-01-01
A revised version of Graphic Normative Analysis Program (GNAP) has been developed to allow maximum flexibility in the evaluation of chemical data by the occasional computer user. GNAP calculates ClPW norms, Thornton and Tuttle's differentiation index, Barth's cations, Niggli values and values for variables defined by the user. Calculated values can be displayed graphically in X-Y plots or ternary diagrams. Plotting can be done on a line printer or Calcomp plotter with either weight percent or mole percent data. Modifications in the original program give the user some control over normative calculations for each sample. The number of user-defined variables that can be created from the data has been increased from ten to fifteen. Plotting and calculations can be based on the original data, data adjusted to sum to 100 percent, or data adjusted to sum to 100 percent without water. Analyses for which norms were previously not computable are now computed with footnotes that show excesses or deficiencies in oxides (or volatiles) not accounted for by the norm. This report contains a listing of the computer program, an explanation of the use of the program, and the two sample problems.
Solving inverse problems with the unfolding program TRUEE: Examples in astroparticle physics
Milke, Natalie; Klepser, Stefan; Mazin, Daniel; Blobel, Volker; Rhode, Wolfgang; 10.1016/j.nima.2012.08.105
2012-01-01
The unfolding program TRUEE is a software package for the numerical solution of inverse problems. The algorithm was fi?rst applied in the FORTRAN77 program RUN. RUN is an event-based unfolding algorithm which makes use of the Tikhonov regularization. It has been tested and compared to di?fferent unfolding applications and stood out with notably stable results and reliable error estimation. TRUEE is a conversion of RUN to C++, which works within the powerful ROOT framework. The program has been extended for more user-friendliness and delivers unfolding results which are identical to RUN. Beside the simplicity of the installation of the software and the generation of graphics, there are new functions, which facilitate the choice of unfolding parameters and observables for the user. In this paper, we introduce the new unfolding program and present its performance by applying it to two exemplary data sets from astroparticle physics, taken with the MAGIC telescopes and the IceCube neutrino detector, respectively.
Pragmatic geometric model evaluation
Pamer, Robert
2015-04-01
Quantification of subsurface model reliability is mathematically and technically demanding as there are many different sources of uncertainty and some of the factors can be assessed merely in a subjective way. For many practical applications in industry or risk assessment (e. g. geothermal drilling) a quantitative estimation of possible geometric variations in depth unit is preferred over relative numbers because of cost calculations for different scenarios. The talk gives an overview of several factors that affect the geometry of structural subsurface models that are based upon typical geological survey organization (GSO) data like geological maps, borehole data and conceptually driven construction of subsurface elements (e. g. fault network). Within the context of the trans-European project "GeoMol" uncertainty analysis has to be very pragmatic also because of different data rights, data policies and modelling software between the project partners. In a case study a two-step evaluation methodology for geometric subsurface model uncertainty is being developed. In a first step several models of the same volume of interest have been calculated by omitting successively more and more input data types (seismic constraints, fault network, outcrop data). The positions of the various horizon surfaces are then compared. The procedure is equivalent to comparing data of various levels of detail and therefore structural complexity. This gives a measure of the structural significance of each data set in space and as a consequence areas of geometric complexity are identified. These areas are usually very data sensitive hence geometric variability in between individual data points in these areas is higher than in areas of low structural complexity. Instead of calculating a multitude of different models by varying some input data or parameters as it is done by Monte-Carlo-simulations, the aim of the second step of the evaluation procedure (which is part of the ongoing work) is to
Geometric singular perturbation theory in biological practice
Hek, G.
2010-01-01
Geometric singular perturbation theory is a useful tool in the analysis of problems with a clear separation in time scales. It uses invariant manifolds in phase space in order to understand the global structure of the phase space or to construct orbits with desired properties. This paper explains an
Geometric Algorithms for Part Orienting and Probing
Panahi, F.
2015-01-01
In this thesis, detailed solutions are presented to several problems dealing with geometric shape and orientation of an object in the field of robotics and automation. We first have considered a general model for shape variations that allows variation along the entire boundary of an object, both in
Geometric Computations on Indecisive and Uncertain Points
Jorgensen, Allan; Phillips, Jeff M
2012-01-01
We study computing geometric problems on uncertain points. An uncertain point is a point that does not have a fixed location, but rather is described by a probability distribution. When these probability distributions are restricted to a finite number of locations, the points are called indecisive points. In particular, we focus on geometric shape-fitting problems and on building compact distributions to describe how the solutions to these problems vary with respect to the uncertainty in the points. Our main results are: (1) a simple and efficient randomized approximation algorithm for calculating the distribution of any statistic on uncertain data sets; (2) a polynomial, deterministic and exact algorithm for computing the distribution of answers for any LP-type problem on an indecisive point set; and (3) the development of shape inclusion probability (SIP) functions which captures the ambient distribution of shapes fit to uncertain or indecisive point sets and are admissible to the two algorithmic constructi...
Approximate dynamic programming recurrence relations for a hybrid optimal control problem
Lu, W.; Ferrari, S.; Fierro, R.; Wettergren, T. A.
2012-06-01
This paper presents a hybrid approximate dynamic programming (ADP) method for a hybrid dynamic system (HDS) optimal control problem, that occurs in many complex unmanned systems which are implemented via a hybrid architecture, regarding robot modes or the complex environment. The HDS considered in this paper is characterized by a well-known three-layer hybrid framework, which includes a discrete event controller layer, a discrete-continuous interface layer, and a continuous state layer. The hybrid optimal control problem (HOCP) is to nd the optimal discrete event decisions and the optimal continuous controls subject to a deterministic minimization of a scalar function regarding the system state and control over time. Due to the uncertainty of environment and complexity of the HOCP, the cost-to-go cannot be evaluated before the HDS explores the entire system state space; as a result, the optimal control, neither continuous nor discrete, is not available ahead of time. Therefore, ADP is adopted to learn the optimal control while the HDS is exploring the environment, because of the online advantage of ADP method. Furthermore, ADP can break the curses of dimensionality which other optimizing methods, such as dynamic programming (DP) and Markov decision process (MDP), are facing due to the high dimensions of HOCP.
Serna, Maria; Trevisan, Luca; Xhafa, Fatos
We present parallel approximation algorithms for maximization problems expressible by integer linear programs of a restricted syntactic form introduced by Barland et al. [BKT96]. One of our motivations was to show whether the approximation results in the framework of Barland et al. holds in the parallel setting. Our results are a confirmation of this, and thus we have a new common framework for both computational settings. Also, we prove almost tight non-approximability results, thus solving a main open question of Barland et al. We obtain the results through the constraint satisfaction problem over multi-valued domains, for which we show non-approximability results and develop parallel approximation algorithms. Our parallel approximation algorithms are based on linear programming and random rounding; they are better than previously known sequential algorithms. The non-approximability results are based on new recent progress in the fields of Probabilistically Checkable Proofs and Multi-Prover One-Round Proof Systems [Raz95, Hås97, AS97, RS97].
Preparing staff for problem-based learning: Outcomes of a comprehensive faculty development program
Directory of Open Access Journals (Sweden)
Lisa Angelique Lim
2014-07-01
Full Text Available This study reports an investigation into the impact of a structured foundational staff development program on new academics in their role as classroom tutors in a problem-based learning (PBL environment. The program aims to pro vide a systematic framework to share knowledge, skills and attitudes necessary for new a cademics to be competent and confident tutors who can provide valued and valuable learning experiences for students’ learning in a PBL environment. To measure the outcomes of this pr ogram, Kirkpatrick’s (1994 framework was adopted, and outcomes were evaluated according to reaction, learning, and behavior. Quantitative data were collected in the form of stu dent feedback scores, tutor confidence, and attitudes toward teaching, while a post-program sur vey was used to collect qualitative data. The results indicate that the program had brought a bout gains in knowledge regarding principles and/or strategies of self-directed learn ing, as well as a detectable change in academics’ orientation towards teaching and learnin g to a more developmental perspective. Moreover, participants noted that they were able to apply their learning in terms of promoting key student behaviors in PBL, such as collaborative learning. The evaluation suggests that, for the successful implementation of PBL, it is importa nt for a structured foundational training program to address not only the essential elements of PBL, but also the role of the tutor, especially in terms of addressing the teaching beli efs of staff, and helping them to adapt to the constructivist belief system embedded in the PBL en vironment.
Gulland, E.-K.; Veenendaal, B.; Schut, A. G. T.
2012-07-01
Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc) disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive learning resources and
Problem based learning - 'Bringing everything together' - A strategy for Graduate Nurse Programs.
Vittrup, Ann-Charlotte; Davey, Anna
2010-03-01
This article discusses a case study that was initiated by a Graduate Nurse Coordinator of an acute care inpatient hospital in Australia. It outlines the conceptualisation and creative implementation of a structured group problem based learning activity which was a component of a Graduate Nurse Program. The learning activity was based on the beliefs that knowledge acquisition today is an active process and should focus on the learner developing strategies to obtain, review and manage information. The learning activity implemented in this case study was valuable as it recognised the benefits that can be gained for the Graduate Nurse by ensuring the context of their teaching and learning activities is grounded in practical experiences. The learning activity aimed to prepare Graduate Nurses to cope with the multiple challenges faced as they enter the nursing profession by enhancing their skills of inquiry, problem solving and reasoning. The evaluation of this case study found that the incorporation of structured group problem based learning did promote the achievement of these educational outcomes with Graduate Nurses displaying critical thinking, clinical judgment and knowledge acquisition skills. An unexpected benefit of this activity for Graduate Nurses was the enhancement of clinical practice behaviours, such as communication and interactive skills. This case study describes the positive outcomes not only for Graduates Nurses in the application of their learning but also the wider benefits which can be gained for the organisation, patient care standards and the health care team. It is anticipated that this article will be an inspiration to others who are interested in implementing innovative teaching strategies into Graduate Nurse Programs.
GEOMETRIC TURBULENCE IN GENERAL RELATIVITY
Directory of Open Access Journals (Sweden)
Trunev A. P.
2015-03-01
Full Text Available The article presents the simulation results of the metric of elementary particles, atoms, stars and galaxies in the general theory of relativity and Yang-Mills theory. We have shown metrics and field equations describing the transition to turbulence. The problems of a unified field theory with the turbulent fluctuations of the metric are considered. A transition from the Einstein equations to the diffusion equation and the Schrödinger equation in quantum mechanics is shown. Ther are examples of metrics in which the field equations are reduced to a single equation, it changes type depending on the equation of state. These examples can be seen as a transition to the geometric turbulence. It is shown that the field equations in general relativity can be reduced to a hyperbolic, elliptic or parabolic type. The equation of parabolic type describing the perturbations of the gravitational field on the scale of stars, galaxies and clusters of galaxies, which is a generalization of the theory of gravitation Newton-Poisson in case of Riemannian geometry, taking into account the curvature of space-time has been derived. It was found that the geometric turbulence leads to an exchange between regions of different scale. Under turbulent exchange material formed of two types of clusters, having positive and negative energy density that corresponds to the classical and quantum particle motion respectively. These results allow us to answer the question about the origin of the quantum theory
几何非线性新梁柱单元及结构程序设计%A geometric nonlinear new beam-column element and structure program design
Institute of Scientific and Technical Information of China (English)
张俊峰; 王利娟; 郝际平; 李天
2011-01-01
基于更新拉格朗日构形的增量虚位移原理,在其势能项中引入了全部6个应力分量,采用可计人单元剪切变形影响的三次多项式插值函数,详细推导了考虑剪切变形及翘曲的空间梁一柱单元几何非线性切线刚度矩阵.根据面向对象的程序设计思想,将整个有限元域划分为8个基本类,在单元基类的基础上派生了新的单元类,采用C++语言编制了面向对象的空间钢结构分析程序.几何非线性算例分析结果表明,本文提出的理论分析方法和计算程序是正确的和高效的.%According to the increment virtual displacement principle based on the updated Lagrange configuration,the potential energy associated with all six stress components was taken into account. The cubic interpolation function which can be used to consider the shear deformation effects has been applied to derive the geometrical nonlinear stiffness matrix of the space beam-column element considering the shear deformation and warping effects. Based on the object-oriented design conception, the finite element analysis domain is divided into eight classes. A new class is derived from the base element class. Using C+ + language,the spatial steel frame advanced analysis program is complied. Numerical examples including both geometric and material nonlinearities are used to demonstrate the accuracy and efficiency of the proposed analytical method and computer program.
Optimal decisions principles of programming
Lange, Oskar
1971-01-01
Optimal Decisions: Principles of Programming deals with all important problems related to programming.This book provides a general interpretation of the theory of programming based on the application of the Lagrange multipliers, followed by a presentation of the marginal and linear programming as special cases of this general theory. The praxeological interpretation of the method of Lagrange multipliers is also discussed.This text covers the Koopmans' model of transportation, geometric interpretation of the programming problem, and nature of activity analysis. The solution of t
On the location selection problem using analytic hierarchy process and multi-choice goal programming
Ho, Hui-Ping; Chang, Ching-Ter; Ku, Cheng-Yuan
2013-01-01
Location selection is a crucial decision in cost/benefit analysis of restaurants, coffee shops and others. However, it is difficult to be solved because there are many conflicting multiple goals in the problem of location selection. In order to solve the problem, this study integrates analytic hierarchy process (AHP) and multi-choice goal programming (MCGP) as a decision aid to obtain an appropriate house from many alternative locations that better suit the preferences of renters under their needs. This study obtains weights from AHP and implements it upon each goal using MCGP for the location selection problem. According to the function of multi-aspiration provided by MCGP, decision makers can set multi-aspiration for each location goal to rank the candidate locations. Compared to the unaided selection processes, the integrated approach of AHP and MCGP is a better scientific and efficient method than traditional methods in finding a suitable location for buying or renting a house for business, especially under multiple qualitative and quantitative criteria within a shorter evaluation time. In addition, a real case is provided to demonstrate the usefulness of the proposed method. The results show that the proposed method is able to provide better quality decision than normal manual methods.
Learning to solve planning problems efficiently by means of genetic programming.
Aler, R; Borrajo, D; Isasi, P
2001-01-01
Declarative problem solving, such as planning, poses interesting challenges for Genetic Programming (GP). There have been recent attempts to apply GP to planning that fit two approaches: (a) using GP to search in plan space or (b) to evolve a planner. In this article, we propose to evolve only the heuristics to make a particular planner more efficient. This approach is more feasible than (b) because it does not have to build a planner from scratch but can take advantage of already existing planning systems. It is also more efficient than (a) because once the heuristics have been evolved, they can be used to solve a whole class of different planning problems in a planning domain, instead of running GP for every new planning problem. Empirical results show that our approach (EvoCK) is able to evolve heuristics in two planning domains (the blocks world and the logistics domain) that improve PRODIGY4.0 performance. Additionally, we experiment with a new genetic operator --Instance-Based Crossover--that is able to use traces of the base planner as raw genetic material to be injected into the evolving population.
Directory of Open Access Journals (Sweden)
Yulia V. Dementieva
2016-01-01
Full Text Available The aim of the study is the description of the main problems of formation of the student’s electronic portfolio in the conditions of realization of Federal State Educational Standards of the Higher Education (FSES of HE.Methods.Theoretical analysis of scientific literature concerning the subject under discussion; monitoring of existing practices in modern Russian Universities procedures for the formation and maintenance of students electronic portfolio.Results. The author describes the main problems of the electronic students’ portfolio formation; some ways of solving described problems are offered.Scientific novelty concludes in the formation of key ideas of the electronic students’ portfolio based on the understanding of requirements of Federal State Educational Standards of Higher Education for the results of mastering educational programs. They are the formation of general cultural, general professional and professional competences.Practical significance. The researching results will become the theoretical basis for the systematic organization of the process of creating and maintaining an electronic students’ portfolio during the whole period of their studying at the university; the researching results can become a basis for methodological developments.
Satellite Video Stabilization with Geometric Distortion
Directory of Open Access Journals (Sweden)
WANG Xia
2016-02-01
Full Text Available There is an exterior orientation difference in each satellite video frame, and the corresponding points have different image locations in adjacent frames images which has geometric distortion. So the projection model, affine model and other classical image stabilization registration model cannot accurately describe the relationship between adjacent frames. This paper proposes a new satellite video image stabilization method with geometric distortion to solve the problem, based on the simulated satellite video, we verify the feasibility and accuracy of proposed satellite video stabilization method.
Frè, Pietro Giuseppe
2013-01-01
‘Gravity, a Geometrical Course’ presents general relativity (GR) in a systematic and exhaustive way, covering three aspects that are homogenized into a single texture: i) the mathematical, geometrical foundations, exposed in a self consistent contemporary formalism, ii) the main physical, astrophysical and cosmological applications, updated to the issues of contemporary research and observations, with glimpses on supergravity and superstring theory, iii) the historical development of scientific ideas underlying both the birth of general relativity and its subsequent evolution. The book is divided in two volumes. Volume One is dedicated to the development of the theory and basic physical applications. It guides the reader from the foundation of special relativity to Einstein field equations, illustrating some basic applications in astrophysics. A detailed account of the historical and conceptual development of the theory is combined with the presentation of its mathematical foundations. Differe...
Bestvina, Mladen; Vogtmann, Karen
2014-01-01
Geometric group theory refers to the study of discrete groups using tools from topology, geometry, dynamics and analysis. The field is evolving very rapidly and the present volume provides an introduction to and overview of various topics which have played critical roles in this evolution. The book contains lecture notes from courses given at the Park City Math Institute on Geometric Group Theory. The institute consists of a set of intensive short courses offered by leaders in the field, designed to introduce students to exciting, current research in mathematics. These lectures do not duplicate standard courses available elsewhere. The courses begin at an introductory level suitable for graduate students and lead up to currently active topics of research. The articles in this volume include introductions to CAT(0) cube complexes and groups, to modern small cancellation theory, to isometry groups of general CAT(0) spaces, and a discussion of nilpotent genus in the context of mapping class groups and CAT(0) gro...
Dynamics in geometrical confinement
Kremer, Friedrich
2014-01-01
This book describes the dynamics of low molecular weight and polymeric molecules when they are constrained under conditions of geometrical confinement. It covers geometrical confinement in different dimensionalities: (i) in nanometer thin layers or self supporting films (1-dimensional confinement) (ii) in pores or tubes with nanometric diameters (2-dimensional confinement) (iii) as micelles embedded in matrices (3-dimensional) or as nanodroplets.The dynamics under such conditions have been a much discussed and central topic in the focus of intense worldwide research activities within the last two decades. The present book discusses how the resulting molecular mobility is influenced by the subtle counterbalance between surface effects (typically slowing down molecular dynamics through attractive guest/host interactions) and confinement effects (typically increasing the mobility). It also explains how these influences can be modified and tuned, e.g. through appropriate surface coatings, film thicknesses or pore...
Geometric Time Delay Interferometry
Vallisneri, Michele
2005-01-01
The space-based gravitational-wave observatory LISA, a NASA-ESA mission to be launched after 2012, will achieve its optimal sensitivity using Time Delay Interferometry (TDI), a LISA-specific technique needed to cancel the otherwise overwhelming laser noise in the inter-spacecraft phase measurements. The TDI observables of the Michelson and Sagnac types have been interpreted physically as the virtual measurements of a synthesized interferometer. In this paper, I present Geometric TDI, a new an...
Geometric unsharpness calculations
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Anderson, D.J. [International Training and Education Group (INTEG), Oakville, Ontario (Canada)
2008-07-15
The majority of radiographers' geometric unsharpness calculations are normally performed with a mathematical formula. However, a majority of codes and standards refer to the use of a nomograph for this calculation. Upon first review, the use of a nomograph appears more complicated but with a few minutes of study and practice it can be just as effective. A review of this article should provide enlightenment. (author)
Geometric Stochastic Resonance
Ghosh, Pulak Kumar; Savel'ev, Sergey E; Nori, Franco
2015-01-01
A Brownian particle moving across a porous membrane subject to an oscillating force exhibits stochastic resonance with properties which strongly depend on the geometry of the confining cavities on the two sides of the membrane. Such a manifestation of stochastic resonance requires neither energetic nor entropic barriers, and can thus be regarded as a purely geometric effect. The magnitude of this effect is sensitive to the geometry of both the cavities and the pores, thus leading to distinctive optimal synchronization conditions.
Geometrically Consistent Mesh Modification
Bonito, A.
2010-01-01
A new paradigm of adaptivity is to execute refinement, coarsening, and smoothing of meshes on manifolds with incomplete information about their geometry and yet preserve position and curvature accuracy. We refer to this collectively as geometrically consistent (GC) mesh modification. We discuss the concept of discrete GC, show the failure of naive approaches, and propose and analyze a simple algorithm that is GC and accuracy preserving. © 2010 Society for Industrial and Applied Mathematics.
Geometric properties of eigenfunctions
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Jakobson, D; Nadirashvili, N [McGill University, Montreal, Quebec (Canada); Toth, John [University of Chicago, Chicago, Illinois (United States)
2001-12-31
We give an overview of some new and old results on geometric properties of eigenfunctions of Laplacians on Riemannian manifolds. We discuss properties of nodal sets and critical points, the number of nodal domains, and asymptotic properties of eigenfunctions in the high-energy limit (such as weak * limits, the rate of growth of L{sup p} norms, and relationships between positive and negative parts of eigenfunctions)
Geometric theory of information
2014-01-01
This book brings together geometric tools and their applications for Information analysis. It collects current and many uses of in the interdisciplinary fields of Information Geometry Manifolds in Advanced Signal, Image & Video Processing, Complex Data Modeling and Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control, Statistics on Manifolds, Machine Learning, Speech/sound recognition, and natural language treatment which are also substantially relevant for the industry.
Perspective: Geometrically frustrated assemblies
Grason, Gregory M.
2016-09-01
This perspective will overview an emerging paradigm for self-organized soft materials, geometrically frustrated assemblies, where interactions between self-assembling elements (e.g., particles, macromolecules, proteins) favor local packing motifs that are incompatible with uniform global order in the assembly. This classification applies to a broad range of material assemblies including self-twisting protein filament bundles, amyloid fibers, chiral smectics and membranes, particle-coated droplets, curved protein shells, and phase-separated lipid vesicles. In assemblies, geometric frustration leads to a host of anomalous structural and thermodynamic properties, including heterogeneous and internally stressed equilibrium structures, self-limiting assembly, and topological defects in the equilibrium assembly structures. The purpose of this perspective is to (1) highlight the unifying principles and consequences of geometric frustration in soft matter assemblies; (2) classify the known distinct modes of frustration and review corresponding experimental examples; and (3) describe outstanding questions not yet addressed about the unique properties and behaviors of this broad class of systems.
Lloyd, Seth
2012-01-01
This letter analyzes the limits that quantum mechanics imposes on the accuracy to which spacetime geometry can be measured. By applying the fundamental physical bounds to measurement accuracy to ensembles of clocks and signals moving in curved spacetime -- e.g., the global positioning system -- I derive a covariant version of the quantum geometric limit: the total number of ticks of clocks and clicks of detectors that can be contained in a four volume of spacetime of radius r and temporal extent t is less than or equal to rt/\\pi x_P t_P, where x_P, t_P are the Planck length and time. The quantum geometric limit bounds the number of events or `ops' that can take place in a four-volume of spacetime: each event is associated with a Planck-scale area. Conversely, I show that if each quantum event is associated with such an area, then Einstein's equations must hold. The quantum geometric limit is consistent with and complementary to the holographic bound which limits the number of bits that can exist within a spat...
Govender, I.; Govender, D.; Havenga, M.; Mentz, E.; Breed, B.; Dignum, F.; Dignum, V.
2014-01-01
The difficulty of learning to program has long been identified amongst novices. This study explored the benefits of teaching a problem solving strategy by comparing students’ perceptions and attitudes towards problem solving before and after the strategy was implemented in secondary schools. Based o
Hawken, Leanne S.; O'Neill, Robert E.; MacLeod, K. Sandra
2011-01-01
The Behavior Education Program (BEP) is a check-in, check-out intervention implemented with students who are at-risk for engaging in more severe problem behavior. Previous research with middle and elementary school students found that the BEP was more effective with students who had adult attention maintained problem behavior. The purposes of this…
A O(n^8) X O(n^7) Linear Programming Model of the Traveling Salesman Problem
Diaby, Moustapha
2008-01-01
In this paper, we present a new linear programming (LP) formulation of the Traveling Salesman Problem (TSP). The proposed model has O(n^8) variables and O(n^7) constraints, where n is the number of cities. Our numerical experimentation shows that computational times for the proposed linear program are several orders of magnitude smaller than those for the existing model [3].
de Graaf, I.; Speetjens, P.; Smit, F.; de Wolff, M.; Tavecchio, L.
2008-01-01
The Triple P Positive Parenting Program is a multilevel parenting program to prevent and offer treatment for severe behavioral, emotional, and developmental problems in children. The aim of this meta-analysis is to assess the effectiveness of Triple P Level 4 interventions in the management of behav
de Graaf, I.; Speetjens, P.; Smit, F.; de Wolff, M.; Tavecchio, L.
2008-01-01
The Triple P Positive Parenting Program is a multilevel parenting program to prevent and offer treatment for severe behavioral, emotional, and developmental problems in children. The aim of this meta-analysis is to assess the effectiveness of Triple P Level 4 interventions in the management of
Geometric diffusion of quantum trajectories.
Yang, Fan; Liu, Ren-Bao
2015-07-16
A quantum object can acquire a geometric phase (such as Berry phases and Aharonov-Bohm phases) when evolving along a path in a parameter space with non-trivial gauge structures. Inherent to quantum evolutions of wavepackets, quantum diffusion occurs along quantum trajectories. Here we show that quantum diffusion can also be geometric as characterized by the imaginary part of a geometric phase. The geometric quantum diffusion results from interference between different instantaneous eigenstate pathways which have different geometric phases during the adiabatic evolution. As a specific example, we study the quantum trajectories of optically excited electron-hole pairs in time-reversal symmetric insulators, driven by an elliptically polarized terahertz field. The imaginary geometric phase manifests itself as elliptical polarization in the terahertz sideband generation. The geometric quantum diffusion adds a new dimension to geometric phases and may have applications in many fields of physics, e.g., transport in topological insulators and novel electro-optical effects.
Geometrically nonlinear creeping mathematic models of shells with variable thickness
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V.M. Zhgoutov
2012-08-01
Full Text Available Calculations of strength, stability and vibration of shell structures play an important role in the design of modern devices machines and structures. However, the behavior of thin-walled structures of variable thickness during which geometric nonlinearity, lateral shifts, viscoelasticity (creep of the material, the variability of the profile take place and thermal deformation starts up is not studied enough.In this paper the mathematical deformation models of variable thickness shells (smoothly variable and ribbed shells, experiencing either mechanical load or permanent temperature field and taking into account the geometrical nonlinearity, creeping and transverse shear, were developed. The refined geometrical proportions for geometrically nonlinear and steadiness problems are given.
A Color Image Watermarking Scheme Resistant against Geometrical Attacks
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Y. Xing
2010-04-01
Full Text Available The geometrical attacks are still a problem for many digital watermarking algorithms at present. In this paper, we propose a watermarking algorithm for color images resistant to geometrical distortions (rotation and scaling. The singular value decomposition is used for watermark embedding and extraction. The log-polar map- ping (LPM and phase correlation method are used to register the position of geometrical distortion suffered by the watermarked image. Experiments with different kinds of color images and watermarks demonstrate that the watermarking algorithm is robust to common image processing attacks, especially geometrical attacks.
Singularity Analysis of Geometric Constraint Systems
Institute of Scientific and Technical Information of China (English)
彭小波; 陈立平; 周凡利; 周济
2002-01-01
Singularity analysis is an important subject of the geometric constraint sat-isfaction problem. In this paper, three kinds of singularities are described and corresponding identification methods are presented for both under-constrained systems and over-constrained systems. Another special but common singularity for under-constrained geometric systems, pseudo-singularity, is analyzed. Pseudo-singularity is caused by a variety of constraint match ing of under-constrained systems and can be removed by improving constraint distribution. To avoid pseudo-singularity and decide redundant constraints adaptively, a differentiation algo rithm is proposed in the paper. Its correctness and efficiency have been validated through its practical applications in a 2D/3D geometric constraint solver CBA.
Algebraic geometric codes with applications
Institute of Scientific and Technical Information of China (English)
CHEN Hao
2007-01-01
The theory of linear error-correcting codes from algebraic geomet-ric curves (algebraic geometric (AG) codes or geometric Goppa codes) has been well-developed since the work of Goppa and Tsfasman, Vladut, and Zink in 1981-1982. In this paper we introduce to readers some recent progress in algebraic geometric codes and their applications in quantum error-correcting codes, secure multi-party computation and the construction of good binary codes.
Geometrical families of mechanically stable granular packings
Gao, Guo-Jie; Blawzdziewicz, Jerzy; O'Hern, Corey S.
2009-12-01
We enumerate and classify nearly all of the possible mechanically stable (MS) packings of bidipserse mixtures of frictionless disks in small sheared systems. We find that MS packings form continuous geometrical families, where each family is defined by its particular network of particle contacts. We also monitor the dynamics of MS packings along geometrical families by applying quasistatic simple shear strain at zero pressure. For small numbers of particles (N16 , we observe an increase in the period and random splittings of the trajectories caused by bifurcations in configuration space. We argue that the ratio of the splitting and contraction rates in large systems will determine the distribution of MS-packing geometrical families visited in steady state. This work is part of our long-term research program to develop a master-equation formalism to describe macroscopic slowly driven granular systems in terms of collections of small subsystems.
Karjalainen, Piia; Santalahti, Pälvi; Sihvo, Sinikka
2016-01-01
In this systematic review it will be evaluated whether parent-targeted programs teaching positive methods of upbringing and interaction are effective in the reduction and prevention of conduct disorders and behavioral problems in children belonging to a risk group. Altogether 29 European studies on parent-targeted programs were selected for the review. Most of the examined methods were based on the social learning theory and the cognitive behavior theory. The majority of the studies proved that long-term programs of 8 to 20 weeks'duration are effective in the reduction of behavioral problems and conduct disorders of childhood.
Generalizations of fuzzy linguistic control points in geometric design
Sallehuddin, M. H.; Wahab, A. F.; Gobithaasan, R. U.
2014-07-01
Control points are geometric primitives that play an important role in designing the geometry curve and surface. When these control points are blended with some basis functions, there are several geometric models such as Bezier, B-spline and NURBS(Non-Uniform Rational B-Spline) will be produced. If the control points are defined by the theory of fuzzy sets, then fuzzy geometric models are produced. But the fuzzy geometric models can only solve the problem of uncertainty complex. This paper proposes a new definition of fuzzy control points with linguistic terms. When the fuzzy control points with linguistic terms are blended with basis functions, then a fuzzy linguistic geometric model is produced. This paper ends with some numerical examples illustrating linguistic control attributes of fuzzy geometric models.
Developing a Novel Multi-objective Programming Model for Personnel Assignment Problem
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Mehdi Seifbarghy
2014-05-01
Full Text Available The assignment of personnel to the right positions in order to increase organization's performance is one of the most crucial tasks in human resource management. In this paper, personnel assignment problem is formulated as a multi-objective binary integer programming model in which skills, level of satisfaction and training cost of personnel are considered simultaneously in productive company. The purpose of this model is to obtain the best matching between candidates and positions. In this model, a set of methods such as a group analytic hierarchy process (GAHP, Shannon entropy, coefficient of variation (CV and fuzzy logic are used to calculate the weights of evaluation criteria, weights of position and coefficient of objective functions. This proposed model can rationalize the subjective judgments of decision makers with mathematic models.
Analysis and presentation of experimental results with examples, problems and programs
Christodoulides, Costas
2017-01-01
This book is intended as a guide to the analysis and presentation of experimental results. It develops various techniques for the numerical processing of experimental data, using basic statistical methods and the theory of errors. After presenting basic theoretical concepts, the book describes the methods by which the results can be presented, both numerically and graphically. The book is divided into three parts, of roughly equal length, addressing the theory, the analysis of data, and the presentation of results. Examples are given and problems are solved using the Excel, Origin, Python and R software packages. In addition, programs in all four languages are made available to readers, allowing them to use them in analyzing and presenting the results of their own experiments. Subjects are treated at a level appropriate for undergraduate students in the natural sciences, but this book should also appeal to anyone whose work involves dealing with experimental results.
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Touil Achraf
2016-01-01
Full Text Available In this paper, a bi-objective mixed integer programming model is proposed to deal with the production-distribution problem found in a dairy company in Morocco. The supply chain containing three echelons: multi-sites, multi-distribution centers and multi-customers. The model seeks to integrate two conflicting simultaneous objectives: maximizing benefit by considering the shelf life of products and the total cost (quantitative objective, including production, storage, and distribution, as well as maximizing the service level (qualitative objective, which relates to providing satisfactory services to customers. This is subject to several technological constraints that typically arise in the dairy industry, such as sequence-dependent changeover time, machine speed and storage capacity. Due to imprecise aspiration levels of goals, an interactive approach is proposed based on fuzzy goal additive variants to find an efficient compromise solution. Numerical results are reported to demonstrate the efficiency and applicability of the proposed model.