Generalized Benders’ Decomposition for topology optimization problems

DEFF Research Database (Denmark)

Munoz Queupumil, Eduardo Javier; Stolpe, Mathias

2011-01-01

) problems with discrete design variables to global optimality. We present the theoretical aspects of the method, including a proof of finite convergence and conditions for obtaining global optimal solutions. The method is also linked to, and compared with, an Outer-Approximation approach and a mixed 0......–1 semi definite programming formulation of the considered problem. Several ways to accelerate the method are suggested and an implementation is described. Finally, a set of truss topology optimization problems are numerically solved to global optimality.......This article considers the non-linear mixed 0–1 optimization problems that appear in topology optimization of load carrying structures. The main objective is to present a Generalized Benders’ Decomposition (GBD) method for solving single and multiple load minimum compliance (maximum stiffness...

A non-linear branch and cut method for solving discrete minimum compliance problems to global optimality

DEFF Research Database (Denmark)

Stolpe, Mathias; Bendsøe, Martin P.

2007-01-01

This paper present some initial results pertaining to a search for globally optimal solutions to a challenging benchmark example proposed by Zhou and Rozvany. This means that we are dealing with global optimization of the classical single load minimum compliance topology design problem with a fixed...... finite element discretization and with discrete design variables. Global optimality is achieved by the implementation of some specially constructed convergent nonlinear branch and cut methods, based on the use of natural relaxations and by applying strengthening constraints (linear valid inequalities......) and cuts....

Global optima for the Zhou–Rozvany problem

DEFF Research Database (Denmark)

Stolpe, Mathias; Bendsøe, Martin P.

2011-01-01

We consider the minimum compliance topology design problem with a volume constraint and discrete design variables. In particular, our interest is to provide global optimal designs to a challenging benchmark example proposed by Zhou and Rozvany. Global optimality is achieved by an implementation o...... algorithms, we find global optimal designs for several values on the available volume. These designs can be used to validate other methods and heuristics for the considered class of problems....

A DE-Based Scatter Search for Global Optimization Problems

Directory of Open Access Journals (Sweden)

Kun Li

2015-01-01

Full Text Available This paper proposes a hybrid scatter search (SS algorithm for continuous global optimization problems by incorporating the evolution mechanism of differential evolution (DE into the reference set updated procedure of SS to act as the new solution generation method. This hybrid algorithm is called a DE-based SS (SSDE algorithm. Since different kinds of mutation operators of DE have been proposed in the literature and they have shown different search abilities for different kinds of problems, four traditional mutation operators are adopted in the hybrid SSDE algorithm. To adaptively select the mutation operator that is most appropriate to the current problem, an adaptive mechanism for the candidate mutation operators is developed. In addition, to enhance the exploration ability of SSDE, a reinitialization method is adopted to create a new population and subsequently construct a new reference set whenever the search process of SSDE is trapped in local optimum. Computational experiments on benchmark problems show that the proposed SSDE is competitive or superior to some state-of-the-art algorithms in the literature.

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

Directory of Open Access Journals (Sweden)

Liang Shen

2017-01-01

Full Text Available There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K-shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

Global optimization of discrete truss topology design problems using a parallel cut-and-branch method

DEFF Research Database (Denmark)

Rasmussen, Marie-Louise Højlund; Stolpe, Mathias

2008-01-01

the physics, and the cuts (Combinatorial Benders’ and projected Chvátal–Gomory) come from an understanding of the particular mathematical structure of the reformulation. The impact of a stronger representation is investigated on several truss topology optimization problems in two and three dimensions.......The subject of this article is solving discrete truss topology optimization problems with local stress and displacement constraints to global optimum. We consider a formulation based on the Simultaneous ANalysis and Design (SAND) approach. This intrinsically non-convex problem is reformulated...

Inchworm movement of two rings switching onto a thread by biased Brownian diffusion represent a three-body problem.

Science.gov (United States)

Benson, Christopher R; Maffeo, Christopher; Fatila, Elisabeth M; Liu, Yun; Sheetz, Edward G; Aksimentiev, Aleksei; Singharoy, Abhishek; Flood, Amar H

2018-05-07

The coordinated motion of many individual components underpins the operation of all machines. However, despite generations of experience in engineering, understanding the motion of three or more coupled components remains a challenge, known since the time of Newton as the "three-body problem." Here, we describe, quantify, and simulate a molecular three-body problem of threading two molecular rings onto a linear molecular thread. Specifically, we use voltage-triggered reduction of a tetrazine-based thread to capture two cyanostar macrocycles and form a [3]pseudorotaxane product. As a consequence of the noncovalent coupling between the cyanostar rings, we find the threading occurs by an unexpected and rare inchworm-like motion where one ring follows the other. The mechanism was derived from controls, analysis of cyclic voltammetry (CV) traces, and Brownian dynamics simulations. CVs from two noncovalently interacting rings match that of two covalently linked rings designed to thread via the inchworm pathway, and they deviate considerably from the CV of a macrocycle designed to thread via a stepwise pathway. Time-dependent electrochemistry provides estimates of rate constants for threading. Experimentally derived parameters (energy wells, barriers, diffusion coefficients) helped determine likely pathways of motion with rate-kinetics and Brownian dynamics simulations. Simulations verified intercomponent coupling could be separated into ring-thread interactions for kinetics, and ring-ring interactions for thermodynamics to reduce the three-body problem to a two-body one. Our findings provide a basis for high-throughput design of molecular machinery with multiple components undergoing coupled motion.

Convex analysis and global optimization

CERN Document Server

Tuy, Hoang

2016-01-01

This book presents state-of-the-art results and methodologies in modern global optimization, and has been a staple reference for researchers, engineers, advanced students (also in applied mathematics), and practitioners in various fields of engineering. The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come. Updates for this new edition include: · Discussion of modern approaches to minimax, fixed point, and equilibrium theorems, and to nonconvex optimization; · Increased focus on dealing more efficiently with ill-posed problems of global optimization, particularly those with hard constraints;

problems; · A complete revision of the chapter on nonconvex quadratic programming...

Dynamic thread assignment in web server performance optimization

NARCIS (Netherlands)

van der Weij, W.; Bhulai, S.; van der Mei, R.D.

2009-01-01

Popular web sites are expected to handle huge number of requests concurrently within a reasonable time frame. The performance of these web sites is largely dependent on effective thread management of their web servers. Although the implementation of static and dynamic thread policies is common

Global optimization methods for engineering design

Science.gov (United States)

Arora, Jasbir S.

1990-01-01

The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.

Arsenic contamination in food chain: Thread to global food security

Science.gov (United States)

Kashyap, C. A.

2016-12-01

The supply of good quality food is a necessity for economic and social health of urban and rural population. Over the last several decades groundwater contamination in developing countries has assumed dangerous levels as a result millions of people are at risk. This is so particularly with respect to arsenic that has registered high concentration in groundwater in countries like India and Bangladesh. The arsenic content in groundwater varies from 10 to 780 µg/L, which is far above the levels for drinking water standards prescribed by World Health Organization (WHO). Currently arsenic has entered in food chain due to irrigation with arsenic contaminated water. In the present study reports the arsenic contamination in groundwater that is being used for irrigating paddy in Manipur and West Bengal. The arsenic content in irrigation water is 475 µg/L and 780 µg/L in Manipur and West Bengal, respectively. In order to assess the effect of such waters on the rice crop, we collected rice plant from Manipur and determined the arsenic content in roots, stem, and grain. The arsenic content in grain varies from 110 to 190 mg/kg while the limit of arsenic intake by humans is 10 mg/kg (WHO). This problem is not confine to the area, it spread global level, and rice being cultivated in these regions is export to the other countries like USA, Middle East and Europe and will be thread to global food security.

Evolutionary global optimization, manifolds and applications

CERN Document Server

Aguiar e Oliveira Junior, Hime

2016-01-01

This book presents powerful techniques for solving global optimization problems on manifolds by means of evolutionary algorithms, and shows in practice how these techniques can be applied to solve real-world problems. It describes recent findings and well-known key facts in general and differential topology, revisiting them all in the context of application to current optimization problems. Special emphasis is put on game theory problems. Here, these problems are reformulated as constrained global optimization tasks and solved with the help of Fuzzy ASA. In addition, more abstract examples, including minimizations of well-known functions, are also included. Although the Fuzzy ASA approach has been chosen as the main optimizing paradigm, the book suggests that other metaheuristic methods could be used as well. Some of them are introduced, together with their advantages and disadvantages. Readers should possess some knowledge of linear algebra, and of basic concepts of numerical analysis and probability theory....

Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem

Directory of Open Access Journals (Sweden)

Ibidun Christiana Obagbuwa

2016-09-01

Full Text Available The Cockroach Swarm Optimization (CSO algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully. The original CSO algorithm and its variants operate mainly in continuous search space and cannot solve binary-coded optimization problems directly. Many optimization problems have their decision variables in binary. Binary Cockroach Swarm Optimization (BCSO is proposed in this paper to tackle such problems and was evaluated on the popular Traveling Salesman Problem (TSP, which is considered to be an NP-hard Combinatorial Optimization Problem (COP. A transfer function was employed to map a continuous search space CSO to binary search space. The performance of the proposed algorithm was tested firstly on benchmark functions through simulation studies and compared with the performance of existing binary particle swarm optimization and continuous space versions of CSO. The proposed BCSO was adapted to TSP and applied to a set of benchmark instances of symmetric TSP from the TSP library. The results of the proposed Binary Cockroach Swarm Optimization (BCSO algorithm on TSP were compared to other meta-heuristic algorithms.

Matlab enhanced multi-threaded tomography optimization sequence (MEMTOS)

International Nuclear Information System (INIS)

Lum, Edward S.; Pope, Chad L.

2016-01-01

Highlights: • Monte Carlo simulation of spent nuclear fuel assembly neutron computed tomography. • Optimized parallel calculations conducted from within the MATLAB environment. • Projection difference technique used to identify anomalies in spent nuclear fuel assemblies. - Abstract: One challenge associated with spent nuclear fuel assemblies is the lack of non-destructive analysis techniques to determine if fuel pins have been removed or replaced or if there are significant defects associated with fuel pins deep within a fuel assembly. Neutron computed tomography is a promising technique for addressing these qualitative issues. Monte Carlo simulation of spent nuclear fuel neutron computed tomography allows inexpensive process investigation and optimization. The main purpose of this work is to provide a fully automated advanced simulation framework for the analysis of spent nuclear fuel inspection using neutron computed tomography. The simulation framework, called Matlab Enhanced Multi-Threaded Tomography Optimization Sequence (MEMTOS) not only automates the simulation process, but also generates superior tomography image results. MEMTOS is written in the MATLAB scripting language and addresses file management, parallel Monte Carlo execution, results extraction, and tomography image generation. This paper describes the mathematical basis for neutron computed tomography, the Monte Carlo technique used to simulate neutron computed tomography, and the overall tomography simulation optimization algorithm. Sequence results presented include overall simulation speed enhancement, tomography and image results obtained for Experimental Breeder Reactor II spent fuel assemblies and light water reactor fuel assemblies. Optimization using a projection difference technique are also described.

Essays and surveys in global optimization

CERN Document Server

Audet, Charles; Savard, Giles

2005-01-01

Global optimization aims at solving the most general problems of deterministic mathematical programming. In addition, once the solutions are found, this methodology is also expected to prove their optimality. With these difficulties in mind, global optimization is becoming an increasingly powerful and important methodology. This book is the most recent examination of its mathematical capability, power, and wide ranging solutions to many fields in the applied sciences.

Conference on Convex Analysis and Global Optimization

CERN Document Server

Pardalos, Panos

2001-01-01

There has been much recent progress in global optimization algo­ rithms for nonconvex continuous and discrete problems from both a theoretical and a practical perspective. Convex analysis plays a fun­ damental role in the analysis and development of global optimization algorithms. This is due essentially to the fact that virtually all noncon­ vex optimization problems can be described using differences of convex functions and differences of convex sets. A conference on Convex Analysis and Global Optimization was held during June 5 -9, 2000 at Pythagorion, Samos, Greece. The conference was honoring the memory of C. Caratheodory (1873-1950) and was en­ dorsed by the Mathematical Programming Society (MPS) and by the Society for Industrial and Applied Mathematics (SIAM) Activity Group in Optimization. The conference was sponsored by the European Union (through the EPEAEK program), the Department of Mathematics of the Aegean University and the Center for Applied Optimization of the University of Florida, by th...

Global Optimization Based on the Hybridization of Harmony Search and Particle Swarm Optimization Methods

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2014-01-01

Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.

Mobile Thread Task Manager

Science.gov (United States)

Clement, Bradley J.; Estlin, Tara A.; Bornstein, Benjamin J.

2013-01-01

The Mobile Thread Task Manager (MTTM) is being applied to parallelizing existing flight software to understand the benefits and to develop new techniques and architectural concepts for adapting software to multicore architectures. It allocates and load-balances tasks for a group of threads that migrate across processors to improve cache performance. In order to balance-load across threads, the MTTM augments a basic map-reduce strategy to draw jobs from a global queue. In a multicore processor, memory may be "homed" to the cache of a specific processor and must be accessed from that processor. The MTTB architecture wraps access to data with thread management to move threads to the home processor for that data so that the computation follows the data in an attempt to avoid L2 cache misses. Cache homing is also handled by a memory manager that translates identifiers to processor IDs where the data will be homed (according to rules defined by the user). The user can also specify the number of threads and processors separately, which is important for tuning performance for different patterns of computation and memory access. MTTM efficiently processes tasks in parallel on a multiprocessor computer. It also provides an interface to make it easier to adapt existing software to a multiprocessor environment.

Loading and Contact Stress Analysis on the Thread Teeth in Tubing and Casing Premium Threaded Connection

Directory of Open Access Journals (Sweden)

Honglin Xu

2014-01-01

Full Text Available Loading and contact stress distribution on the thread teeth in tubing and casing premium threaded connections are of great importance for design optimization, pretightening force control, and thread failure prevention. This paper proposes an analytical method based on the elastic mechanics. This is quite different from other papers, which mainly rely on finite element analysis. The differential equation of load distribution on the thread teeth was established according to equal pitch of the engaged thread after deformation and solved by finite difference method. Furthermore, the relation between load acting on each engaged thread and mean contact stress on its load flank is set up based on the geometric description of thread surface. By comparison, this new analytical method with the finite element analysis for a modified API 177.8 mm premium threaded connection is approved. Comparison of the contact stress on the last engaged thread between analytical model and FEM shows that the accuracy of analytical model will decline with the increase of pretightening force after the material enters into plastic deformation. However, the analytical method can meet the needs of engineering to some extent because its relative error is about 6.2%~18.1% for the in-service level of pretightening force.

A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem

Directory of Open Access Journals (Sweden)

Mio Horai

2016-01-01

Full Text Available We propose a new method for the specific nonlinear and nonconvex global optimization problem by using a linear relaxation technique. To simplify the specific nonlinear and nonconvex optimization problem, we transform the problem to the lower linear relaxation form, and we solve the linear relaxation optimization problem by the Branch and Bound Algorithm. Under some reasonable assumptions, the global convergence of the algorithm is certified for the problem. Numerical results show that this method is more efficient than the previous methods.

Global optimization and simulated annealing

NARCIS (Netherlands)

Dekkers, A.; Aarts, E.H.L.

1988-01-01

In this paper we are concerned with global optimization, which can be defined as the problem of finding points on a bounded subset of Rn in which some real valued functionf assumes its optimal (i.e. maximal or minimal) value. We present a stochastic approach which is based on the simulated annealing

On benchmarking Stochastic Global Optimization Algorithms

NARCIS (Netherlands)

Hendrix, E.M.T.; Lancinskas, A.

2015-01-01

A multitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which

A Novel Consensus-Based Particle Swarm Optimization-Assisted Trust-Tech Methodology for Large-Scale Global Optimization.

Science.gov (United States)

Zhang, Yong-Feng; Chiang, Hsiao-Dong

2017-09-01

A novel three-stage methodology, termed the "consensus-based particle swarm optimization (PSO)-assisted Trust-Tech methodology," to find global optimal solutions for nonlinear optimization problems is presented. It is composed of Trust-Tech methods, consensus-based PSO, and local optimization methods that are integrated to compute a set of high-quality local optimal solutions that can contain the global optimal solution. The proposed methodology compares very favorably with several recently developed PSO algorithms based on a set of small-dimension benchmark optimization problems and 20 large-dimension test functions from the CEC 2010 competition. The analytical basis for the proposed methodology is also provided. Experimental results demonstrate that the proposed methodology can rapidly obtain high-quality optimal solutions that can contain the global optimal solution. The scalability of the proposed methodology is promising.

Conference on "State of the Art in Global Optimization : Computational Methods and Applications"

CERN Document Server

Pardalos, P

1996-01-01

Optimization problems abound in most fields of science, engineering, and technology. In many of these problems it is necessary to compute the global optimum (or a good approximation) of a multivariable function. The variables that define the function to be optimized can be continuous and/or discrete and, in addition, many times satisfy certain constraints. Global optimization problems belong to the complexity class of NP-hard prob­ lems. Such problems are very difficult to solve. Traditional descent optimization algorithms based on local information are not adequate for solving these problems. In most cases of practical interest the number of local optima increases, on the aver­ age, exponentially with the size of the problem (number of variables). Furthermore, most of the traditional approaches fail to escape from a local optimum in order to continue the search for the global solution. Global optimization has received a lot of attention in the past ten years, due to the success of new algorithms for solvin...

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

Science.gov (United States)

Krohling, Renato A; Coelho, Leandro dos Santos

2006-12-01

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

Dedicated memory structure holding data for detecting available worker thread(s) and informing available worker thread(s) of task(s) to execute

Energy Technology Data Exchange (ETDEWEB)

Chiu, George L.; Eichenberger, Alexandre E.; O' Brien, John K. P.

2016-12-13

The present disclosure relates generally to a dedicated memory structure (that is, hardware device) holding data for detecting available worker thread(s) and informing available worker thread(s) of task(s) to execute.

Topology optimization of Channel flow problems

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan; Sigmund, Ole; Haber, R. B.

2005-01-01

function which measures either some local aspect of the velocity field or a global quantity, such as the rate of energy dissipation. We use the finite element method to model the flow, and we solve the optimization problem with a gradient-based math-programming algorithm that is driven by analytical......This paper describes a topology design method for simple two-dimensional flow problems. We consider steady, incompressible laminar viscous flows at low to moderate Reynolds numbers. This makes the flow problem non-linear and hence a non-trivial extension of the work of [Borrvall&Petersson 2002......]. Further, the inclusion of inertia effects significantly alters the physics, enabling solutions of new classes of optimization problems, such as velocity--driven switches, that are not addressed by the earlier method. Specifically, we determine optimal layouts of channel flows that extremize a cost...

An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.

Science.gov (United States)

Islam, Md Monjurul; Singh, Hemant Kumar; Ray, Tapabrata; Sinha, Ankur

2017-01-01

Bilevel optimization, as the name reflects, deals with optimization at two interconnected hierarchical levels. The aim is to identify the optimum of an upper-level  leader problem, subject to the optimality of a lower-level follower problem. Several problems from the domain of engineering, logistics, economics, and transportation have an inherent nested structure which requires them to be modeled as bilevel optimization problems. Increasing size and complexity of such problems has prompted active theoretical and practical interest in the design of efficient algorithms for bilevel optimization. Given the nested nature of bilevel problems, the computational effort (number of function evaluations) required to solve them is often quite high. In this article, we explore the use of a Memetic Algorithm (MA) to solve bilevel optimization problems. While MAs have been quite successful in solving single-level optimization problems, there have been relatively few studies exploring their potential for solving bilevel optimization problems. MAs essentially attempt to combine advantages of global and local search strategies to identify optimum solutions with low computational cost (function evaluations). The approach introduced in this article is a nested Bilevel Memetic Algorithm (BLMA). At both upper and lower levels, either a global or a local search method is used during different phases of the search. The performance of BLMA is presented on twenty-five standard test problems and two real-life applications. The results are compared with other established algorithms to demonstrate the efficacy of the proposed approach.

Global Optimization Ensemble Model for Classification Methods

Science.gov (United States)

Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

2014-01-01

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

Global Optimization Ensemble Model for Classification Methods

Directory of Open Access Journals (Sweden)

Hina Anwar

2014-01-01

Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.

A Global Optimization Algorithm for Sum of Linear Ratios Problem

OpenAIRE

Yuelin Gao; Siqiao Jin

2013-01-01

We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the c...

Toward solving the sign problem with path optimization method

Science.gov (United States)

Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira

2017-12-01

We propose a new approach to circumvent the sign problem in which the integration path is optimized to control the sign problem. We give a trial function specifying the integration path in the complex plane and tune it to optimize the cost function which represents the seriousness of the sign problem. We call it the path optimization method. In this method, we do not need to solve the gradient flow required in the Lefschetz-thimble method and then the construction of the integration-path contour arrives at the optimization problem where several efficient methods can be applied. In a simple model with a serious sign problem, the path optimization method is demonstrated to work well; the residual sign problem is resolved and precise results can be obtained even in the region where the global sign problem is serious.

Global optimization and sensitivity analysis

International Nuclear Information System (INIS)

Cacuci, D.G.

1990-01-01

A new direction for the analysis of nonlinear models of nuclear systems is suggested to overcome fundamental limitations of sensitivity analysis and optimization methods currently prevalent in nuclear engineering usage. This direction is toward a global analysis of the behavior of the respective system as its design parameters are allowed to vary over their respective design ranges. Presented is a methodology for global analysis that unifies and extends the current scopes of sensitivity analysis and optimization by identifying all the critical points (maxima, minima) and solution bifurcation points together with corresponding sensitivities at any design point of interest. The potential applicability of this methodology is illustrated with test problems involving multiple critical points and bifurcations and comprising both equality and inequality constraints

Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm

Directory of Open Access Journals (Sweden)

V. D. Sulimov

2014-01-01

Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search

A Simple But Effective Canonical Dual Theory Unified Algorithm for Global Optimization

OpenAIRE

Zhang, Jiapu

2011-01-01

Numerical global optimization methods are often very time consuming and could not be applied for high-dimensional nonconvex/nonsmooth optimization problems. Due to the nonconvexity/nonsmoothness, directly solving the primal problems sometimes is very difficult. This paper presents a very simple but very effective canonical duality theory (CDT) unified global optimization algorithm. This algorithm has convergence is proved in this paper. More important, for this CDT-unified algorithm, numerous...

Complicated problem solution techniques in optimal parameter searching

International Nuclear Information System (INIS)

Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.

1992-01-01

An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs

4th International Conference on Frontiers in Global Optimization

CERN Document Server

Pardalos, Panos

2004-01-01

Global Optimization has emerged as one of the most exciting new areas of mathematical programming. Global optimization has received a wide attraction from many fields in the past few years, due to the success of new algorithms for addressing previously intractable problems from diverse areas such as computational chemistry and biology, biomedicine, structural optimization, computer sciences, operations research, economics, and engineering design and control. This book contains refereed invited papers submitted at the 4th international confer­ ence on Frontiers in Global Optimization held at Santorini, Greece during June 8-12, 2003. Santorini is one of the few sites of Greece, with wild beauty created by the explosion of a volcano which is in the middle of the gulf of the island. The mystic landscape with its numerous mult-extrema, was an inspiring location particularly for researchers working on global optimization. The three previous conferences on "Recent Advances in Global Opti­ mization", "State-of-the-...

Global approach to the n-dimensional traveling salesman problem: Application to the optimization of crystallographic data collection

Energy Technology Data Exchange (ETDEWEB)

Weinrach, J.B.; Bennett, D.W.

1987-12-01

An algorithm for the optimization of data collection time has been written and a subsequent computer program tested for diffractometer systems. The program, which utilizes a global statistical approach to the traveling salesman problem, yields reasonable solutions in a relatively short time. The algorithm has been successful in treating very large data sets (up to 4000 points) in three dimensions with subsequent time savings of ca 30%.

Acceleration techniques in the univariate Lipschitz global optimization

Science.gov (United States)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.; De Franco, Angela

2016-10-01

Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions.

3rd World Congress on Global Optimization in Engineering & Science

CERN Document Server

Ruan, Ning; Xing, Wenxun; WCGO-III; Advances in Global Optimization

2015-01-01

This proceedings volume addresses advances in global optimization—a multidisciplinary research field that deals with the analysis, characterization, and computation of global minima and/or maxima of nonlinear, non-convex, and nonsmooth functions in continuous or discrete forms. The volume contains selected papers from the third biannual World Congress on Global Optimization in Engineering & Science (WCGO), held in the Yellow Mountains, Anhui, China on July 8-12, 2013. The papers fall into eight topical sections: mathematical programming; combinatorial optimization; duality theory; topology optimization; variational inequalities and complementarity problems; numerical optimization; stochastic models and simulation; and complex simulation and supply chain analysis.

Deterministic global optimization an introduction to the diagonal approach

CERN Document Server

Sergeyev, Yaroslav D

2017-01-01

This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed...

A Global Optimization Algorithm for Sum of Linear Ratios Problem

Directory of Open Access Journals (Sweden)

Yuelin Gao

2013-01-01

Full Text Available We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the convergence of the algorithm is proved. Numerical experiments are reported to show the effectiveness of the proposed algorithm.

Towards Fast Reverse Time Migration Kernels using Multi-threaded Wavefront Diamond Tiling

KAUST Repository

Malas, T.

2015-09-13

Today’s high-end multicore systems are characterized by a deep memory hierarchy, i.e., several levels of local and shared caches, with limited size and bandwidth per core. The ever-increasing gap between the processor and memory speed will further exacerbate the problem and has lead the scientific community to revisit numerical software implementations to better suit the underlying memory subsystem for performance (data reuse) as well as energy efficiency (data locality). The authors propose a novel multi-threaded wavefront diamond blocking (MWD) implementation in the context of stencil computations, which represents the core operation for seismic imaging in oil industry. The stencil diamond formulation introduces temporal blocking for high data reuse in the upper cache levels. The wavefront optimization technique ensures data locality by allowing multiple threads to share common adjacent point stencil. Therefore, MWD is able to take up the aforementioned challenges by alleviating the cache size limitation and releasing pressure from the memory bandwidth. Performance comparisons are shown against the optimized 25-point stencil standard seismic imaging scheme using spatial and temporal blocking and demonstrate the effectiveness of MWD.

Theory and Algorithms for Global/Local Design Optimization

National Research Council Canada - National Science Library

Haftka, Raphael T

2004-01-01

... the component and overall design as well as on exploration of global optimization algorithms. In the former category, heuristic decomposition was followed with proof that it solves the original problem...

The Automated Threaded Fastening Based on On-line Identification

Directory of Open Access Journals (Sweden)

Nicolas Ivan Giannoccaro

2008-11-01

Full Text Available The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.

Global blending optimization of laminated composites with discrete material candidate selection and thickness variation

DEFF Research Database (Denmark)

Sørensen, Søren N.; Stolpe, Mathias

2015-01-01

rate. The capabilities of the method and the effect of active versus inactive manufacturing constraints are demonstrated on several numerical examples of limited size, involving at most 320 binary variables. Most examples are solved to guaranteed global optimality and may constitute benchmark examples...... but is, however, convex in the original mixed binary nested form. Convexity is the foremost important property of optimization problems, and the proposed method can guarantee the global or near-global optimal solution; unlike most topology optimization methods. The material selection is limited...... for popular topology optimization methods and heuristics based on solving sequences of non-convex problems. The results will among others demonstrate that the difficulty of the posed problem is highly dependent upon the composition of the constitutive properties of the material candidates....

A perturbed martingale approach to global optimization

Energy Technology Data Exchange (ETDEWEB)

Sarkar, Saikat [Computational Mechanics Lab, Department of Civil Engineering, Indian Institute of Science, Bangalore 560012 (India); Roy, Debasish, E-mail: royd@civil.iisc.ernet.in [Computational Mechanics Lab, Department of Civil Engineering, Indian Institute of Science, Bangalore 560012 (India); Vasu, Ram Mohan [Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore 560012 (India)

2014-08-01

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as ‘coalescence’ and ‘scrambling’. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. - Highlights: • Evolutionary global optimization is posed as a perturbed martingale problem. • Resulting search via additive updates is a generalization over Gateaux derivatives. • Additional layers of random perturbation help avoid trapping at local extrema. • The approach ensures efficient design space exploration and high accuracy. • The method is numerically assessed via parameter recovery of chaotic oscillators.

Threaded-fastener experience in nuclear power plants

International Nuclear Information System (INIS)

Koo, W.H.

1983-01-01

This report identifies 44 incidents of threaded-fastener degradation and failure in nuclear power plants from October 1964 to March 1982. It provides an overview of some of the threaded-fastener problems that have occurred since 1964. Safety implications of these incidents are discussed, and short-term regulatory actions and ongoing long-term regulatory actions are described. Information included in this report represents the current NRC staff understanding of each issue

LETTER TO THE EDITOR: Constant-time solution to the global optimization problem using Brüschweiler's ensemble search algorithm

Science.gov (United States)

Protopopescu, V.; D'Helon, C.; Barhen, J.

2003-06-01

A constant-time solution of the continuous global optimization problem (GOP) is obtained by using an ensemble algorithm. We show that under certain assumptions, the solution can be guaranteed by mapping the GOP onto a discrete unsorted search problem, whereupon Brüschweiler's ensemble search algorithm is applied. For adequate sensitivities of the measurement technique, the query complexity of the ensemble search algorithm depends linearly on the size of the function's domain. Advantages and limitations of an eventual NMR implementation are discussed.

Path optimization method for the sign problem

Directory of Open Access Journals (Sweden)

Ohnishi Akira

2018-01-01

Full Text Available We propose a path optimization method (POM to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t(f ϵ R and by optimizing f(t to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.

A dynamic global and local combined particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Chen Qunxian

2009-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems, but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems.

Truss topology optimization with discrete design variables — Guaranteed global optimality and benchmark examples

DEFF Research Database (Denmark)

Achtziger, Wolfgang; Stolpe, Mathias

2007-01-01

this problem is well-studied for continuous bar areas, we consider in this study the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single available bar area, i.......e., a 0/1 problem. In contrast to the heuristic methods considered in many other approaches, our goal is to compute guaranteed globally optimal structures. This is done by a branch-and-bound method for which convergence can be proven. In this branch-and-bound framework, lower bounds of the optimal......-integer problems. The main intention of this paper is to provide optimal solutions for single and multiple load benchmark examples, which can be used for testing and validating other methods or heuristics for the treatment of this discrete topology design problem....

Implementation and verification of global optimization benchmark problems

Science.gov (United States)

Posypkin, Mikhail; Usov, Alexander

2017-12-01

The paper considers the implementation and verification of a test suite containing 150 benchmarks for global deterministic box-constrained optimization. A C++ library for describing standard mathematical expressions was developed for this purpose. The library automate the process of generating the value of a function and its' gradient at a given point and the interval estimates of a function and its' gradient on a given box using a single description. Based on this functionality, we have developed a collection of tests for an automatic verification of the proposed benchmarks. The verification has shown that literary sources contain mistakes in the benchmarks description. The library and the test suite are available for download and can be used freely.

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

Science.gov (United States)

Roy, Satadru

Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network

A Comparative Study on Recently-Introduced Nature-Based Global Optimization Methods in Complex Mechanical System Design

Directory of Open Access Journals (Sweden)

Abdulbaset El Hadi Saad

2017-10-01

Full Text Available Advanced global optimization algorithms have been continuously introduced and improved to solve various complex design optimization problems for which the objective and constraint functions can only be evaluated through computation intensive numerical analyses or simulations with a large number of design variables. The often implicit, multimodal, and ill-shaped objective and constraint functions in high-dimensional and “black-box” forms demand the search to be carried out using low number of function evaluations with high search efficiency and good robustness. This work investigates the performance of six recently introduced, nature-inspired global optimization methods: Artificial Bee Colony (ABC, Firefly Algorithm (FFA, Cuckoo Search (CS, Bat Algorithm (BA, Flower Pollination Algorithm (FPA and Grey Wolf Optimizer (GWO. These approaches are compared in terms of search efficiency and robustness in solving a set of representative benchmark problems in smooth-unimodal, non-smooth unimodal, smooth multimodal, and non-smooth multimodal function forms. In addition, four classic engineering optimization examples and a real-life complex mechanical system design optimization problem, floating offshore wind turbines design optimization, are used as additional test cases representing computationally-expensive black-box global optimization problems. Results from this comparative study show that the ability of these global optimization methods to obtain a good solution diminishes as the dimension of the problem, or number of design variables increases. Although none of these methods is universally capable, the study finds that GWO and ABC are more efficient on average than the other four in obtaining high quality solutions efficiently and consistently, solving 86% and 80% of the tested benchmark problems, respectively. The research contributes to future improvements of global optimization methods.

Competing intelligent search agents in global optimization

Energy Technology Data Exchange (ETDEWEB)

Streltsov, S.; Vakili, P. [Boston Univ., MA (United States); Muchnik, I. [Rutgers Univ., Piscataway, NJ (United States)

1996-12-31

In this paper we present a new search methodology that we view as a development of intelligent agent approach to the analysis of complex system. The main idea is to consider search process as a competition mechanism between concurrent adaptive intelligent agents. Agents cooperate in achieving a common search goal and at the same time compete with each other for computational resources. We propose a statistical selection approach to resource allocation between agents that leads to simple and efficient on average index allocation policies. We use global optimization as the most general setting that encompasses many types of search problems, and show how proposed selection policies can be used to improve and combine various global optimization methods.

Optimizing human activity patterns using global sensitivity analysis.

Science.gov (United States)

Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M

2014-12-01

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.

Protein structure recognition: From eigenvector analysis to structural threading method

Science.gov (United States)

Cao, Haibo

In this work, we try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. We found a strong correlation between amino acid sequence and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, we give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part include discussions of interactions among amino acids residues, lattice HP model, and the designablity principle. In the second part, we try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in our eigenvector study of protein contact matrix. We believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, we discuss a threading method based on the correlation between amino acid sequence and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, we list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.

Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method

Energy Technology Data Exchange (ETDEWEB)

Cao, Haibo [Iowa State Univ., Ames, IA (United States)

2003-01-01

In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.

Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method

International Nuclear Information System (INIS)

Haibo Cao

2003-01-01

In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches

Probabilistic thread algebra

NARCIS (Netherlands)

Bergstra, J.A.; Middelburg, C.A.

2015-01-01

We add probabilistic features to basic thread algebra and its extensions with thread-service interaction and strategic interleaving. Here, threads represent the behaviours produced by instruction sequences under execution and services represent the behaviours exhibited by the components of execution

Implementation and verification of global optimization benchmark problems

Directory of Open Access Journals (Sweden)

Posypkin Mikhail

2017-12-01

Full Text Available The paper considers the implementation and verification of a test suite containing 150 benchmarks for global deterministic box-constrained optimization. A C++ library for describing standard mathematical expressions was developed for this purpose. The library automate the process of generating the value of a function and its’ gradient at a given point and the interval estimates of a function and its’ gradient on a given box using a single description. Based on this functionality, we have developed a collection of tests for an automatic verification of the proposed benchmarks. The verification has shown that literary sources contain mistakes in the benchmarks description. The library and the test suite are available for download and can be used freely.

Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

Directory of Open Access Journals (Sweden)

Kanagasabai Lenin

2015-04-01

Full Text Available In this paper, a novel approach Modified Monkey optimization (MMO algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases.  The proposed (MMO algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

Directory of Open Access Journals (Sweden)

Taeuk Kim

2018-01-01

Full Text Available The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS. LADS (Layout-Aware Data Scheduling is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

Method for reinforcing threads in multilayer composite tubes and cylindrical structures

International Nuclear Information System (INIS)

Romanoski, G.R.; Burchell, T.D.

1996-01-01

Multilayer techniques such as: tape wrapping, braiding, and filament winding represent versatile and economical routes for fabricating composite tubes and cylindrical structures. However, multilayer architectures lack the radial reinforcement required to retain threads when the desired means of connection or closure is a threaded joint. This issue was addressed in the development of a filament wound, carbon-carbon composite impact shell for the NASA radioisotope thermoelectric generator. The problem of poor thread shear strength was solved by incorporating a number of radial elements of triangular geometry around the circumference of the thread for the full length of thread engagement. The radial elements significantly increased the shear strength of the threaded joint by transmitting the applied force to the balance of composite structure. This approach is also applicable to ceramic composites

The mathematical model of thread unrolling from a bobbin

Directory of Open Access Journals (Sweden)

S. M. Tenenbaum

2014-01-01

Full Text Available I. Introduction The subject of research in this work is a process of thread unrolling from a bobbin. The mathematical model of this process considering motion of thread peace on a bobbin and unrolled peace is proposed. The dimension of system of differential equations for this model is constant during deploying.The relevance to simulate this process for design of Heliogyro-like solar sails (Heliogyro [1], BMSTU-Sail [2] is proved. The paper briefly characterizes a blade for such solar sail as a simulation object. It proves the possibility for using a flexible thread model for a long blade because of very small blade thickness (less than 10 μm [3] relative to blade width and the phenomena of Koriolis forces [4] that lead to buckling failure of blade flatness.The major features of the proposed model are:-- simulated as a motion of the thread piece both being on a bobbin and its unrolled peace;-- splitting a thread length into nodes does not depend on the demand to ensure a sufficient number of nodes on a single thread turn on the coil;-- because of avoiding a problem of contact between the thread and bobbin a stable integration of motion equations is provided by the conventional Runge-Kutta method of fourth order with a constant step [5];-- in the course of solution the number of freedom degrees (number of motion equation is constant, thereby simplifying a calculation algorithm.The closest mathematical model is proposed in [6].The scientific novelty of this research is the approach to solving the problem of unrolling thread from a bobbin using a constant number of motion equations while preserving real kinematics coiling process.II. Problem formulationIn this section the problem of unrolling thread with length L from a bobbin of radius r is posed while any kind of forces are acting on the unrolled peace of thread. Moreover, the law of bobbin rotation φ(t assumed to be known with the proviso that the model can be modified if φ(t is the result of

Loosening and damage mechanism of thread-joined structures in nuclear power equipment

International Nuclear Information System (INIS)

Tang Hui

1999-01-01

The author proposes a loosening mechanism of thread-joined structures under vibrate environments in the nuclear power equipment and structures, which is on the base of the macro and imperceptible-mechanics analysis. It has answered the problems on the seizing, the adhesive wearing, the generation of cracks, the thread-tooth fracture. So it has a conclusion that the loosening of thread-joined structures is essential trend, in other words, the locking property of thread-pair is failure under vibrate environments

Solving non-standard packing problems by global optimization and heuristics

CERN Document Server

Fasano, Giorgio

2014-01-01

This book results from a long-term research effort aimed at tackling complex non-standard packing issues which arise in space engineering. The main research objective is to optimize cargo loading and arrangement, in compliance with a set of stringent rules. Complicated geometrical aspects are also taken into account, in addition to balancing conditions based on attitude control specifications. Chapter 1 introduces the class of non-standard packing problems studied. Chapter 2 gives a detailed explanation of a general model for the orthogonal packing of tetris-like items in a convex domain. A number of additional conditions are looked at in depth, including the prefixed orientation of subsets of items, the presence of unusable holes, separation planes and structural elements, relative distance bounds as well as static and dynamic balancing requirements. The relative feasibility sub-problem which is a special case that does not have an optimization criterion is discussed in Chapter 3. This setting can be exploit...

Overall bolt stress optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2013-01-01

The state of stress in bolts and nuts with International Organization for Standardization metric thread design is examined and optimized. The assumed failure mode is fatigue, so the applied preload and the load amplitude together with the stress concentrations define the connection strength....... Maximum stress in the bolt is found at the fillet under the head, at the thread start, or at the thread root. To minimize the stress concentration, shape optimization is applied. Nut shape optimization also has a positive effect on the maximum stress. The optimization results show that designing a nut......, which results in a more evenly distribution of load along the engaged thread, has a limited influence on the maximum stress due to the stress concentration at the first thread root. To further reduce the maximum stress, the transition from bolt shank to the thread must be optimized. Stress reduction...

Deterministic global optimization algorithm based on outer approximation for the parameter estimation of nonlinear dynamic biological systems.

Science.gov (United States)

Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano

2012-05-10

The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.

BIOMECHANICAL JUSTIFICATION OF THE THREADED ELEMENT’S FORM OF THE TOTAL HIP ENDOPROSTHESIS’ ACETABULAR COMPONENT

Directory of Open Access Journals (Sweden)

PANCHENKO S. P.

2017-03-01

Full Text Available Abstract. Formulation of the problem. Total hip replacement (THR remains to be responsible for the markable clinical achievements of contemporal orthopaedic surgery [1; 2; 4]. It should be noted, that numerous efforts to create an “ideal” uncemented hip endoprosthesis’ construction were failed, but led into wide diversity of implants. Such a diversity allowes to individualize implant type selection and to improve implant’s survival and total THR’s clinical outcomes [1; 4]. Outcomes mentioned above determine successful application of total hip replacement as a treatment method. Consequently, development of new and improvement of existing hip endoprosthesis’ constructions seems to be of current interest for contemporal orthopaedic surgery. Purpose. To determine optimal parametres of threaded element’s geometry of total hip endoprosthesis’ threaded acetabular component. Conclusion. There were revealed that threaded element model with right-angled triangle transverse section shape seems to be the most effective considering hardness, while the triangle is leaned on the bone massive with its cathetus. At the same time, results of calculations represent pelvic bone stress-strain state during THR quantitavely and stipulate further research.

Theoretical properties of the global optimizer of two layer neural network

OpenAIRE

Boob, Digvijay; Lan, Guanghui

2017-01-01

In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number of parameters is greater than the number of sampled points. We show that for a wide class of differentiable activation functions (this class involves "almost" all functions which are not piecewise linear), we have that first-order optimal solutions satisfy global optimality provided the hidden layer is non-singular. ...

Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems

Science.gov (United States)

Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

2014-01-01

A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. In the proposed local search technique, a potential particle position in the solution search space is collectively constructed by a number of randomly selected particles in the swarm. The number of times the selection is made varies with the dimension of the optimization problem and each selected particle donates the value in the location of its randomly selected dimension from its personal best. After constructing the potential particle position, some local search is done around its neighbourhood in comparison with the current swarm global best position. It is then used to replace the global best particle position if it is found to be better; otherwise no replacement is made. Using some well-studied benchmark problems with low and high dimensions, numerical simulations were used to validate the performance of the improved algorithms. Comparisons were made with four different PSO variants, two of the variants implement different local search technique while the other two do not. Results show that the improved algorithms could obtain better quality solution while demonstrating better convergence velocity and precision, stability, robustness, and global-local search ability than the competing variants. PMID:24723827

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

Directory of Open Access Journals (Sweden)

Shouheng Tuo

Full Text Available Harmony Search (HS and Teaching-Learning-Based Optimization (TLBO as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Application of surrogate-based global optimization to aerodynamic design

CERN Document Server

Pérez, Esther

2016-01-01

Aerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive – this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogat...

Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

Directory of Open Access Journals (Sweden)

Wei Li

2015-01-01

Full Text Available We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems.

Science.gov (United States)

Su, Weixing; Chen, Hanning; Liu, Fang; Lin, Na; Jing, Shikai; Liang, Xiaodan; Liu, Wei

2017-03-01

There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC) for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell's pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

GMG: A Guaranteed, Efficient Global Optimization Algorithm for Remote Sensing.

Energy Technology Data Exchange (ETDEWEB)

D' Helon, CD

2004-08-18

The monocular passive ranging (MPR) problem in remote sensing consists of identifying the precise range of an airborne target (missile, plane, etc.) from its observed radiance. This inverse problem may be set as a global optimization problem (GOP) whereby the difference between the observed and model predicted radiances is minimized over the possible ranges and atmospheric conditions. Using additional information about the error function between the predicted and observed radiances of the target, we developed GMG, a new algorithm to find the Global Minimum with a Guarantee. The new algorithm transforms the original continuous GOP into a discrete search problem, thereby guaranteeing to find the position of the global minimum in a reasonably short time. The algorithm is first applied to the golf course problem, which serves as a litmus test for its performance in the presence of both complete and degraded additional information. GMG is further assessed on a set of standard benchmark functions and then applied to various realizations of the MPR problem.

Optimal stability polynomials for numerical integration of initial value problems

KAUST Repository

Ketcheson, David I.

2013-01-08

We consider the problem of finding optimally stable polynomial approximations to the exponential for application to one-step integration of initial value ordinary and partial differential equations. The objective is to find the largest stable step size and corresponding method for a given problem when the spectrum of the initial value problem is known. The problem is expressed in terms of a general least deviation feasibility problem. Its solution is obtained by a new fast, accurate, and robust algorithm based on convex optimization techniques. Global convergence of the algorithm is proven in the case that the order of approximation is one and in the case that the spectrum encloses a starlike region. Examples demonstrate the effectiveness of the proposed algorithm even when these conditions are not satisfied.

Global WASF-GA: An Evolutionary Algorithm in Multiobjective Optimization to Approximate the Whole Pareto Optimal Front.

Science.gov (United States)

Saborido, Rubén; Ruiz, Ana B; Luque, Mariano

2017-01-01

In this article, we propose a new evolutionary algorithm for multiobjective optimization called Global WASF-GA ( global weighting achievement scalarizing function genetic algorithm), which falls within the aggregation-based evolutionary algorithms. The main purpose of Global WASF-GA is to approximate the whole Pareto optimal front. Its fitness function is defined by an achievement scalarizing function (ASF) based on the Tchebychev distance, in which two reference points are considered (both utopian and nadir objective vectors) and the weight vector used is taken from a set of weight vectors whose inverses are well-distributed. At each iteration, all individuals are classified into different fronts. Each front is formed by the solutions with the lowest values of the ASF for the different weight vectors in the set, using the utopian vector and the nadir vector as reference points simultaneously. Varying the weight vector in the ASF while considering the utopian and the nadir vectors at the same time enables the algorithm to obtain a final set of nondominated solutions that approximate the whole Pareto optimal front. We compared Global WASF-GA to MOEA/D (different versions) and NSGA-II in two-, three-, and five-objective problems. The computational results obtained permit us to conclude that Global WASF-GA gets better performance, regarding the hypervolume metric and the epsilon indicator, than the other two algorithms in many cases, especially in three- and five-objective problems.

Global optimization based on noisy evaluations: An empirical study of two statistical approaches

International Nuclear Information System (INIS)

Vazquez, Emmanuel; Villemonteix, Julien; Sidorkiewicz, Maryan; Walter, Eric

2008-01-01

The optimization of the output of complex computer codes has often to be achieved with a small budget of evaluations. Algorithms dedicated to such problems have been developed and compared, such as the Expected Improvement algorithm (El) or the Informational Approach to Global Optimization (IAGO). However, the influence of noisy evaluation results on the outcome of these comparisons has often been neglected, despite its frequent appearance in industrial problems. In this paper, empirical convergence rates for El and IAGO are compared when an additive noise corrupts the result of an evaluation. IAGO appears more efficient than El and various modifications of El designed to deal with noisy evaluations. Keywords. Global optimization; computer simulations; kriging; Gaussian process; noisy evaluations.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems

Directory of Open Access Journals (Sweden)

Weixing Su

2017-03-01

Full Text Available There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell’s pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

Parallel and Cooperative Particle Swarm Optimizer for Multimodal Problems

Directory of Open Access Journals (Sweden)

Geng Zhang

2015-01-01

Full Text Available Although the original particle swarm optimizer (PSO method and its related variant methods show some effectiveness for solving optimization problems, it may easily get trapped into local optimum especially when solving complex multimodal problems. Aiming to solve this issue, this paper puts forward a novel method called parallel and cooperative particle swarm optimizer (PCPSO. In case that the interacting of the elements in D-dimensional function vector X=[x1,x2,…,xd,…,xD] is independent, cooperative particle swarm optimizer (CPSO is used. Based on this, the PCPSO is presented to solve real problems. Since the dimension cannot be split into several lower dimensional search spaces in real problems because of the interacting of the elements, PCPSO exploits the cooperation of two parallel CPSO algorithms by orthogonal experimental design (OED learning. Firstly, the CPSO algorithm is used to generate two locally optimal vectors separately; then the OED is used to learn the merits of these two vectors and creates a better combination of them to generate further search. Experimental studies on a set of test functions show that PCPSO exhibits better robustness and converges much closer to the global optimum than several other peer algorithms.

Fast Gaussian kernel learning for classification tasks based on specially structured global optimization.

Science.gov (United States)

Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen

2014-09-01

For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Novel Hybrid Firefly Algorithm for Global Optimization.

Directory of Open Access Journals (Sweden)

Lina Zhang

Full Text Available Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA, is proposed by combining the advantages of both the firefly algorithm (FA and differential evolution (DE. FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA, differential evolution (DE and particle swarm optimization (PSO in the sense of avoiding local minima and increasing the convergence rate.

Argobots: A Lightweight Low-Level Threading and Tasking Framework

International Nuclear Information System (INIS)

Seo, Sangmin; Amer, Abdelhalim; Balaji, Pavan; Bordage, Cyril; Bosilca, George

2017-01-01

In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, are either too specific to applications or architectures or are not as powerful or flexible. In this article, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by the user or high-level programming model. Here, we describe the design, implementation, and optimization of Argobots and present integrations with three example high-level models: OpenMP, MPI, and co-located I/O service. Evaluations show that (1) Argobots outperforms existing generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency hiding capabilities; and (4) I/O service with Argobots reduces interference with co-located applications, achieving performance competitive with that of the Pthreads version.

Cribellate thread production in spiders: Complex processing of nano-fibres into a functional capture thread.

Science.gov (United States)

Joel, Anna-Christin; Kappel, Peter; Adamova, Hana; Baumgartner, Werner; Scholz, Ingo

2015-11-01

Spider silk production has been studied intensively in the last years. However, capture threads of cribellate spiders employ an until now often unnoticed alternative of thread production. This thread in general is highly interesting, as it not only involves a controlled arrangement of three types of threads with one being nano-scale fibres (cribellate fibres), but also a special comb-like structure on the metatarsus of the fourth leg (calamistrum) for its production. We found the cribellate fibres organized as a mat, enclosing two parallel larger fibres (axial fibres) and forming the typical puffy structure of cribellate threads. Mat and axial fibres are punctiform connected to each other between two puffs, presumably by the action of the median spinnerets. However, this connection alone does not lead to the typical puffy shape of a cribellate thread. Removing the calamistrum, we found a functional capture thread still being produced, but the puffy shape of the thread was lost. Therefore, the calamistrum is not necessary for the extraction or combination of fibres, but for further processing of the nano-scale cribellate fibres. Using data from Uloborus plumipes we were able to develop a model of the cribellate thread production, probably universally valid for cribellate spiders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits

Directory of Open Access Journals (Sweden)

Kajsa Ljungberg

2010-10-01

Full Text Available Kajsa Ljungberg1, Kateryna Mishchenko2, Sverker Holmgren11Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden; 2Department of Mathematics and Physics, Mälardalen University College, Västerås, SwedenAbstract: We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called QTL, and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms.Keywords: global optimization, QTL mapping, DIRECT 

Real-time SHVC software decoding with multi-threaded parallel processing

Science.gov (United States)

Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu

2014-09-01

This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.

Optimal correction and design parameter search by modern methods of rigorous global optimization

International Nuclear Information System (INIS)

Makino, K.; Berz, M.

2011-01-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

Science.gov (United States)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

Neoliberal Optimism: Applying Market Techniques to Global Health.

Science.gov (United States)

Mei, Yuyang

2017-01-01

Global health and neoliberalism are becoming increasingly intertwined as organizations utilize markets and profit motives to solve the traditional problems of poverty and population health. I use field work conducted over 14 months in a global health technology company to explore how the promise of neoliberalism re-envisions humanitarian efforts. In this company's vaccine refrigerator project, staff members expect their investors and their market to allow them to achieve scale and develop accountability to their users in developing countries. However, the translation of neoliberal techniques to the global health sphere falls short of the ideal, as profits are meager and purchasing power remains with donor organizations. The continued optimism in market principles amidst such a non-ideal market reveals the tenacious ideological commitment to neoliberalism in these global health projects.

Acoustic reverse-time migration using GPU card and POSIX thread based on the adaptive optimal finite-difference scheme and the hybrid absorbing boundary condition

Science.gov (United States)

Cai, Xiaohui; Liu, Yang; Ren, Zhiming

2018-06-01

Reverse-time migration (RTM) is a powerful tool for imaging geologically complex structures such as steep-dip and subsalt. However, its implementation is quite computationally expensive. Recently, as a low-cost solution, the graphic processing unit (GPU) was introduced to improve the efficiency of RTM. In the paper, we develop three ameliorative strategies to implement RTM on GPU card. First, given the high accuracy and efficiency of the adaptive optimal finite-difference (FD) method based on least squares (LS) on central processing unit (CPU), we study the optimal LS-based FD method on GPU. Second, we develop the CPU-based hybrid absorbing boundary condition (ABC) to the GPU-based one by addressing two issues of the former when introduced to GPU card: time-consuming and chaotic threads. Third, for large-scale data, the combinatorial strategy for optimal checkpointing and efficient boundary storage is introduced for the trade-off between memory and recomputation. To save the time of communication between host and disk, the portable operating system interface (POSIX) thread is utilized to create the other CPU core at the checkpoints. Applications of the three strategies on GPU with the compute unified device architecture (CUDA) programming language in RTM demonstrate their efficiency and validity.

Optimization of Bolt Stress

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2013-01-01

The state of stress in bolts and nuts with ISO metric thread design is examined and optimized. The assumed failure mode is fatigue so the applied preload and the load amplitude together with the stress concentrations define the connection strength. Maximum stress in the bolt is found at, the fillet...... under the head, at the thread start or at the thread root. To minimize the stress concentration shape optimization is applied....

On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization

Science.gov (United States)

Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

2013-01-01

Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. Researchers have tried to address this shortcoming by modifying LDIW-PSO or proposing new PSO variants. Some of these variants have been claimed to outperform LDIW-PSO. The major goal of this paper is to experimentally establish the fact that LDIW-PSO is very much efficient if its parameters are properly set. First, an experiment was conducted to acquire a percentage value of the search space limits to compute the particle velocity limits in LDIW-PSO based on commonly used benchmark global optimization problems. Second, using the experimentally obtained values, five well-known benchmark optimization problems were used to show the outstanding performance of LDIW-PSO over some of its competitors which have in the past claimed superiority over it. Two other recent PSO variants with different inertia weight strategies were also compared with LDIW-PSO with the latter outperforming both in the simulation experiments conducted. PMID:24324383

The Advanced Thread-Locking Mechanism

Science.gov (United States)

Weiss, Wolfgang

2005-12-01

Locking of threaded members is accomplished by a wide variety of engineering solutions. Generally, in terms of separate locking devices or by built-in locking features such as friction generating means.In regard of space flight vehicles, threaded joints are subject to severe vibration loads during launch, maneuvering, and reentry. This requires fastening systems which are capable to join structural members and attach accessories or equipment in a secure manner. However, manned spacecraft and especially payload components will be subject to installation activity during orbital or interstellar flight maintenance, repair, or mission modification. This, in turn, requires fast separation and engaging of the concerned fasteners, yet providing performance characteristics for high reliable and safe joints.The further described Advanced Thread Locking Mechanism (ATLM) has been developed to combine the merits of both, safe joining technique and a fast installation process. The ATLM uses a freewheel which is securely installed in one part of the threaded member and releasable coupled with the engaged counterpart. While screwing the threaded members together, once coupled, the freewheel will allow free mating of the threaded members including torquing to the desired value. The moment, the pair of threaded fasteners is forced to unscrew (by intended or unintended occurrence of torque in the undoing direction) the freewheel does lock instantly. Disengaging the coupling between the members of the threaded joint takes a separate release action.Owing to the nature of the ATLM, there are a number of design variants ready for implementation.Threaded fasteners in ATLM design are highly recommended for mechanical joints subject to fastening and unfastening during Extra Vehicular Activity (EVA) in course of space flight operations. This is justified through:1. Threaded members mate free running, thus, torque values preset at the wrenching tool are not influenced by varying prevailing

Particle Swarm Optimization for Structural Design Problems

Directory of Open Access Journals (Sweden)

Hamit SARUHAN

2010-02-01

Full Text Available The aim of this paper is to employ the Particle Swarm Optimization (PSO technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. Mechanical engineering design problems are complex activities which are computing capability are more and more required. The most of these problems are solved by conventional mathematical programming techniques that require gradient information. These techniques have several drawbacks from which the main one is becoming trapped in local optima. As an alternative to gradient-based techniques, the PSO does not require the evaluation of gradients of the objective function. The PSO algorithm employs the generation of guided random positions when they search for the global optimum point. The PSO which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. The results obtained by the PSO are compared with Mathematical Programming (MP. It is demonstrated that the PSO performed and obtained better convergence reliability on the global optimum point than the MP. Using the MP, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the PSO.

Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

Directory of Open Access Journals (Sweden)

Ahmet Demir

2017-01-01

Full Text Available In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an important role on providing software related techniques to improve the associated literature. Today, intelligent optimization techniques based on Artificial Intelligence are widely used for optimization problems. The objective of this paper is to provide a comparative study on the employment of classical optimization solutions and Artificial Intelligence solutions for enabling readers to have idea about the potential of intelligent optimization techniques. At this point, two recently developed intelligent optimization algorithms, Vortex Optimization Algorithm (VOA and Cognitive Development Optimization Algorithm (CoDOA, have been used to solve some multidisciplinary optimization problems provided in the source book Thomas' Calculus 11th Edition and the obtained results have compared with classical optimization solutions. 

On the efficiency of chaos optimization algorithms for global optimization

International Nuclear Information System (INIS)

Yang Dixiong; Li Gang; Cheng Gengdong

2007-01-01

Chaos optimization algorithms as a novel method of global optimization have attracted much attention, which were all based on Logistic map. However, we have noticed that the probability density function of the chaotic sequences derived from Logistic map is a Chebyshev-type one, which may affect the global searching capacity and computational efficiency of chaos optimization algorithms considerably. Considering the statistical property of the chaotic sequences of Logistic map and Kent map, the improved hybrid chaos-BFGS optimization algorithm and the Kent map based hybrid chaos-BFGS algorithm are proposed. Five typical nonlinear functions with multimodal characteristic are tested to compare the performance of five hybrid optimization algorithms, which are the conventional Logistic map based chaos-BFGS algorithm, improved Logistic map based chaos-BFGS algorithm, Kent map based chaos-BFGS algorithm, Monte Carlo-BFGS algorithm, mesh-BFGS algorithm. The computational performance of the five algorithms is compared, and the numerical results make us question the high efficiency of the chaos optimization algorithms claimed in some references. It is concluded that the efficiency of the hybrid optimization algorithms is influenced by the statistical property of chaotic/stochastic sequences generated from chaotic/stochastic algorithms, and the location of the global optimum of nonlinear functions. In addition, it is inappropriate to advocate the high efficiency of the global optimization algorithms only depending on several numerical examples of low-dimensional functions

A global optimization algorithm inspired in the behavior of selfish herds.

Science.gov (United States)

Fausto, Fernando; Cuevas, Erik; Valdivia, Arturo; González, Adrián

2017-10-01

In this paper, a novel swarm optimization algorithm called the Selfish Herd Optimizer (SHO) is proposed for solving global optimization problems. SHO is based on the simulation of the widely observed selfish herd behavior manifested by individuals within a herd of animals subjected to some form of predation risk. In SHO, individuals emulate the predatory interactions between groups of prey and predators by two types of search agents: the members of a selfish herd (the prey) and a pack of hungry predators. Depending on their classification as either a prey or a predator, each individual is conducted by a set of unique evolutionary operators inspired by such prey-predator relationship. These unique traits allow SHO to improve the balance between exploration and exploitation without altering the population size. To illustrate the proficiency and robustness of the proposed method, it is compared to other well-known evolutionary optimization approaches such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Differential Evolution (DE), Genetic Algorithms (GA), Crow Search Algorithm (CSA), Dragonfly Algorithm (DA), Moth-flame Optimization Algorithm (MOA) and Sine Cosine Algorithm (SCA). The comparison examines several standard benchmark functions, commonly considered within the literature of evolutionary algorithms. The experimental results show the remarkable performance of our proposed approach against those of the other compared methods, and as such SHO is proven to be an excellent alternative to solve global optimization problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulation of LHC events on a millions threads

Science.gov (United States)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; Papka, M. E.; Benjamin, D. P.

2015-12-01

Demand for Grid resources is expected to double during LHC Run II as compared to Run I; the capacity of the Grid, however, will not double. The HEP community must consider how to bridge this computing gap by targeting larger compute resources and using the available compute resources as efficiently as possible. Argonne's Mira, the fifth fastest supercomputer in the world, can run roughly five times the number of parallel processes that the ATLAS experiment typically uses on the Grid. We ported Alpgen, a serial x86 code, to run as a parallel application under MPI on the Blue Gene/Q architecture. By analysis of the Alpgen code, we reduced the memory footprint to allow running 64 threads per node, utilizing the four hardware threads available per core on the PowerPC A2 processor. Event generation and unweighting, typically run as independent serial phases, are coupled together in a single job in this scenario, reducing intermediate writes to the filesystem. By these optimizations, we have successfully run LHC proton-proton physics event generation at the scale of a million threads, filling two-thirds of Mira.

Two years' outcome of thread lifting with absorbable barbed PDO threads: Innovative score for objective and subjective assessment.

Science.gov (United States)

Ali, Yasser Helmy

2018-02-01

Thread-lifting rejuvenation procedures have evolved again, with the development of absorbable threads. Although they have gained popularity among plastic surgeons and dermatologists, very few articles have been written in literature about absorbable threads. This study aims to evaluate two years' outcome of thread lifting using absorbable barbed threads for facial rejuvenation. Prospective comparative stud both objectively and subjectively and follow-up assessment for 24 months. Thread lifting for face rejuvenation has significant long-lasting effects that include skin lifting from 3-10 mm and high degree of patients' satisfaction with less incidence rate of complications, about 4.8%. Augmented results are obtained when thread lifting is combined with other lifting and rejuvenation modalities. Significant facial rejuvenation is achieved by thread lifting and highly augmented results are observed when they are combined with Botox, fillers, and/or platelet rich plasma (PRP) rejuvenations.

Optimization of hetero-epitaxial growth for the threading dislocation density reduction of germanium epilayers

Science.gov (United States)

Chong, Haining; Wang, Zhewei; Chen, Chaonan; Xu, Zemin; Wu, Ke; Wu, Lan; Xu, Bo; Ye, Hui

2018-04-01

In order to suppress dislocation generation, we develop a "three-step growth" method to heteroepitaxy low dislocation density germanium (Ge) layers on silicon with the MBE process. The method is composed of 3 growth steps: low temperature (LT) seed layer, LT-HT intermediate layer as well as high temperature (HT) epilayer, successively. Threading dislocation density (TDD) of epitaxial Ge layers is measured as low as 1.4 × 106 cm-2 by optimizing the growth parameters. The results of Raman spectrum showed that the internal strain of heteroepitaxial Ge layers is tensile and homogeneous. During the growth of LT-HT intermediate layer, TDD reduction can be obtained by lowering the temperature ramping rate, and high rate deposition maintains smooth surface morphology in Ge epilayer. A mechanism based on thermodynamics is used to explain the TDD and surface morphological dependence on temperature ramping rate and deposition rate. Furthermore, we demonstrate that the Ge layer obtained can provide an excellent platform for III-V materials integrated on Si.

SOCIAL NETWORK OPTIMIZATION A NEW METHAHEURISTIC FOR GENERAL OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Hassan Sherafat

2017-12-01

Full Text Available In the recent years metaheuristics were studied and developed as powerful technics for hard optimization problems. Some of well-known technics in this field are: Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, and Swarm Intelligence, which are applied successfully to many complex optimization problems. In this paper, we introduce a new metaheuristic for solving such problems based on social networks concept, named as Social Network Optimization – SNO. We show that a wide range of np-hard optimization problems may be solved by SNO.

Class and Home Problems: Optimization Problems

Science.gov (United States)

Anderson, Brian J.; Hissam, Robin S.; Shaeiwitz, Joseph A.; Turton, Richard

2011-01-01

Optimization problems suitable for all levels of chemical engineering students are available. These problems do not require advanced mathematical techniques, since they can be solved using typical software used by students and practitioners. The method used to solve these problems forces students to understand the trends for the different terms…

Priorities in the field of international cooperation with the aim of solving global environmental problems

Energy Technology Data Exchange (ETDEWEB)

Kondrat' ev, K.YA.

1993-08-01

Considerations on priorities are presented in connection with the broad development of bilateral and multilateral international cooperation to solve global environmental problems. Emphasis is placed on the problem of global climate change, on optimizing the global climate observation system, and on substantiating the (1) inadequacy of the 'greenhouse' stereotype of global climate warming which has long predominated in Russian cooperation programs, and (2) the need to realize real climatic prorities (the role of biosphere dynamics, the interaction of atmosphere and ocean, cloud cover and radiation, the colloidal nature of the atmosphere, etc.). The thermal balance of the earth and the dynamics of the biosphere are considered as the key problems of global ecodynamics. Particular attention is given to socio-economic aspects of ecology. 62 refs.

Advances in stochastic and deterministic global optimization

CERN Document Server

Zhigljavsky, Anatoly; Žilinskas, Julius

2016-01-01

Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, and scientists in computer science, numerical analysis, optimization, and applied mathematics will be fascinated by the theoretical, computational, and application-oriented aspects of stochastic and deterministic global optimization explored in this book. This volume is dedicated to the 70th birthday of Antanas Žilinskas who is a leading world expert in global optimization. Professor Žilinskas's research has concentrated on studying models for the objective function, the development and implementation of efficient algorithms for global optimization with single and mu...

Ordinal optimization and its application to complex deterministic problems

Science.gov (United States)

Yang, Mike Shang-Yu

1998-10-01

We present in this thesis a new perspective to approach a general class of optimization problems characterized by large deterministic complexities. Many problems of real-world concerns today lack analyzable structures and almost always involve high level of difficulties and complexities in the evaluation process. Advances in computer technology allow us to build computer models to simulate the evaluation process through numerical means, but the burden of high complexities remains to tax the simulation with an exorbitant computing cost for each evaluation. Such a resource requirement makes local fine-tuning of a known design difficult under most circumstances, let alone global optimization. Kolmogorov equivalence of complexity and randomness in computation theory is introduced to resolve this difficulty by converting the complex deterministic model to a stochastic pseudo-model composed of a simple deterministic component and a white-noise like stochastic term. The resulting randomness is then dealt with by a noise-robust approach called Ordinal Optimization. Ordinal Optimization utilizes Goal Softening and Ordinal Comparison to achieve an efficient and quantifiable selection of designs in the initial search process. The approach is substantiated by a case study in the turbine blade manufacturing process. The problem involves the optimization of the manufacturing process of the integrally bladed rotor in the turbine engines of U.S. Air Force fighter jets. The intertwining interactions among the material, thermomechanical, and geometrical changes makes the current FEM approach prohibitively uneconomical in the optimization process. The generalized OO approach to complex deterministic problems is applied here with great success. Empirical results indicate a saving of nearly 95% in the computing cost.

PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

Science.gov (United States)

Chen, Shuangqing; Wei, Lixin; Guan, Bing

2018-01-01

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems. PMID:29675036

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

Science.gov (United States)

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Adaptive control in multi-threaded iterated integration

International Nuclear Information System (INIS)

Doncker, Elise de; Yuasa, Fukuko

2013-01-01

In recent years we have developed a technique for the direct computation of Feynman loop-integrals, which are notorious for the occurrence of integrand singularities. Especially for handling singularities in the interior of the domain, we approximate the iterated integral using an adaptive algorithm in the coordinate directions. We present a novel multi-core parallelization scheme for adaptive multivariate integration, by assigning threads to the rule evaluations in the outer dimensions of the iterated integral. The method ensures a large parallel granularity as each function evaluation by itself comprises an integral over the lower dimensions, while the application of the threads is governed by the adaptive control in the outer level. We give computational results for a test set of 3- to 6-dimensional integrals, where several problems exhibit a loop integral behavior.

Real-time inextensible surgical thread simulation.

Science.gov (United States)

Xu, Lang; Liu, Qian

2018-03-27

This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects. The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations. Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method. Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.

Effect of Thread and Rotating Speed on Material Flow Behavior and Mechanical Properties of Friction Stir Lap Welding Joints

Science.gov (United States)

Ji, Shude; Li, Zhengwei; Zhou, Zhenlu; Wu, Baosheng

2017-10-01

This study focused on the effects of thread on hook and cold lap formation, lap shear property and impact toughness of alclad 2024-T4 friction stir lap welding (FSLW) joints. Except the traditional threaded pin tool (TR-tool), three new tools with different thread locations and orientations were designed. Results showed that thread significantly affected hook, cold lap morphologies and lap shear properties. The tool with tip-threaded pin (T-tool) fabricated joint with flat hook and cold lap, which resulted in shear fracture mode. The tools with bottom-threaded pin (B-tool) eliminated the hook. The tool with reverse-threaded pin (R-tool) widened the stir zone width. When using configuration A, the joints fabricated by the three new tools showed higher failure loads than the joint fabricated by the TR-tool. The joint using the T-tool owned the optimum impact toughness. This study demonstrated the significance of thread during FSLW and provided a reference to optimize tool geometry.

Thread Structure: Rewriting the Hollywood Formula.

Science.gov (United States)

Smith, Evan

2000-01-01

Describes a new nonlinear model that has crept into Hollywood's cinematic repertoire in which multiple story threads comprise the story. Examines how this thread structure differs from ensemble stories. Examines differences between traditionally linear films and films with thread structure regarding character roles and viewer orientation, shifts…

Binary Bees Algorithm - bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem

Science.gov (United States)

Xu, Shuo; Ji, Ze; Truong Pham, Duc; Yu, Fan

2011-11-01

The simultaneous mission assignment and home allocation for hospital service robots studied is a Multidimensional Assignment Problem (MAP) with multiobjectives and multiconstraints. A population-based metaheuristic, the Binary Bees Algorithm (BBA), is proposed to optimize this NP-hard problem. Inspired by the foraging mechanism of honeybees, the BBA's most important feature is an explicit functional partitioning between global search and local search for exploration and exploitation, respectively. Its key parts consist of adaptive global search, three-step elitism selection (constraint handling, non-dominated solutions selection, and diversity preservation), and elites-centred local search within a Hamming neighbourhood. Two comparative experiments were conducted to investigate its single objective optimization, optimization effectiveness (indexed by the S-metric and C-metric) and optimization efficiency (indexed by computational burden and CPU time) in detail. The BBA outperformed its competitors in almost all the quantitative indices. Hence, the above overall scheme, and particularly the searching history-adapted global search strategy was validated.

Control of influence of a thread on a bending of screws

International Nuclear Information System (INIS)

Proskuriakov, N E; Lopa, I V; Trapeznikov, E V

2017-01-01

The influence of the threads and the bending of screw on their moments of inertia of the cross section considered. This problem is actual since existing methods exclude from calculations the influence of supporting the thread, using as the basic geometrical parameter such as the internal diameter of the thread (diameter of cavities). Fundamental difference of a bend of the screw from a bend of a smooth rod consists that moment of inertia of the screw is a variable. It is shown that the change in cross-section moment of inertia along the length of the screw are essential and have periodic character. Analytical interrelation of the bending of the screw and the decreasing of moment of inertia of its cross section is established and equation describing this phenomenon is suggested. The greatest decrease of the moment of inertia occurs in the middle of the screw length, and the lowest - at its ends. Function and approximate coefficients for the main types of thread are proposed, which take into account this change. (paper)

Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions

KAUST Repository

Odat, Enas M.

2011-05-01

The purpose of this dissertation is to present a methodology to model global sequence alignment problem as directed acyclic graph which helps to extract all possible optimal alignments. Moreover, a mechanism to sequentially optimize sequence alignment problem relative to different cost functions is suggested. Sequence alignment is mostly important in computational biology. It is used to find evolutionary relationships between biological sequences. There are many algo- rithms that have been developed to solve this problem. The most famous algorithms are Needleman-Wunsch and Smith-Waterman that are based on dynamic program- ming. In dynamic programming, problem is divided into a set of overlapping sub- problems and then the solution of each subproblem is found. Finally, the solutions to these subproblems are combined into a final solution. In this thesis it has been proved that for two sequences of length m and n over a fixed alphabet, the suggested optimization procedure requires O(mn) arithmetic operations per cost function on a single processor machine. The algorithm has been simulated using C#.Net programming language and a number of experiments have been done to verify the proved statements. The results of these experiments show that the number of optimal alignments is reduced after each step of optimization. Furthermore, it has been verified that as the sequence length increased linearly then the number of optimal alignments increased exponentially which also depends on the cost function that is used. Finally, the number of executed operations increases polynomially as the sequence length increase linearly.

Hagfish slime threads as a biomimetic model for high performance protein fibres

International Nuclear Information System (INIS)

Fudge, Douglas S; Hillis, Sonja; Levy, Nimrod; Gosline, John M

2010-01-01

Textile manufacturing is one of the largest industries in the world, and synthetic fibres represent two-thirds of the global textile market. Synthetic fibres are manufactured from petroleum-based feedstocks, which are becoming increasingly expensive as demand for finite petroleum reserves continues to rise. For the last three decades, spider silks have been held up as a model that could inspire the production of protein fibres exhibiting high performance and ecological sustainability, but unfortunately, artificial spider silks have yet to fulfil this promise. Previous work on the biomechanics of protein fibres from the slime of hagfishes suggests that these fibres might be a superior biomimetic model to spider silks. Based on the fact that the proteins within these 'slime threads' adopt conformations that are similar to those in spider silks when they are stretched, we hypothesized that draw processing of slime threads should yield fibres that are comparable to spider dragline silk in their mechanical performance. Here we show that draw-processed slime threads are indeed exceptionally strong and tough. We also show that post-drawing steps such as annealing, dehydration and covalent cross-linking can dramatically improve the long-term dimensional stability of the threads. The data presented here suggest that hagfish slime threads are a model that should be pursued in the quest to produce fibres that are ecologically sustainable and economically viable.

The effect of thread pattern upon implant osseointegration.

Science.gov (United States)

Abuhussein, Heba; Pagni, Giorgio; Rebaudi, Alberto; Wang, Hom-Lay

2010-02-01

Implant design features such as macro- and micro-design may influence overall implant success. Limited information is currently available. Therefore, it is the purpose of this paper to examine these factors such as thread pitch, thread geometry, helix angle, thread depth and width as well as implant crestal module may affect implant stability. A literature search was conducted using MEDLINE to identify studies, from simulated laboratory models, animal, to human, related to this topic using the keywords of implant thread, implant macrodesign, thread pitch, thread geometry, helix angle, thread depth, thread width and implant crestal module. The results showed how thread geometry affects the distribution of stress forces around the implant. A decreased thread pitch may positively influence implant stability. Excess helix angles in spite of a faster insertion may jeopardize the ability of implants to sustain axial load. Deeper threads seem to have an important effect on the stabilization in poorer bone quality situations. The addition of threads or microthreads up to the crestal module of an implant might provide a potential positive contribution on bone-to to-implant contact as well as on the preservation of marginal bone; nonetheless this remains to be determined. Appraising the current literature on this subject and combining existing data to verify the presence of any association between the selected characteristics may be critical in the achievement of overall implant success.

Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

OpenAIRE

Ahmet Demir; Utku kose

2017-01-01

In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an...

Identification of metabolic system parameters using global optimization methods

Directory of Open Access Journals (Sweden)

Gatzke Edward P

2006-01-01

Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.

Guaranteed Discrete Energy Optimization on Large Protein Design Problems.

Science.gov (United States)

Simoncini, David; Allouche, David; de Givry, Simon; Delmas, Céline; Barbe, Sophie; Schiex, Thomas

2015-12-08

In Computational Protein Design (CPD), assuming a rigid backbone and amino-acid rotamer library, the problem of finding a sequence with an optimal conformation is NP-hard. In this paper, using Dunbrack's rotamer library and Talaris2014 decomposable energy function, we use an exact deterministic method combining branch and bound, arc consistency, and tree-decomposition to provenly identify the global minimum energy sequence-conformation on full-redesign problems, defining search spaces of size up to 10(234). This is achieved on a single core of a standard computing server, requiring a maximum of 66GB RAM. A variant of the algorithm is able to exhaustively enumerate all sequence-conformations within an energy threshold of the optimum. These proven optimal solutions are then used to evaluate the frequencies and amplitudes, in energy and sequence, at which an existing CPD-dedicated simulated annealing implementation may miss the optimum on these full redesign problems. The probability of finding an optimum drops close to 0 very quickly. In the worst case, despite 1,000 repeats, the annealing algorithm remained more than 1 Rosetta unit away from the optimum, leading to design sequences that could differ from the optimal sequence by more than 30% of their amino acids.

Threaded biliary inside stents are a safe and effective therapeutic option in cases of malignant hilar obstruction.

Science.gov (United States)

Inatomi, Osamu; Bamba, Shigeki; Shioya, Makoto; Mochizuki, Yosuke; Ban, Hiromitsu; Tsujikawa, Tomoyuki; Saito, Yasuharu; Andoh, Akira; Fujiyama, Yoshihide

2013-02-14

Although endoscopic biliary stents have been accepted as part of palliative therapy for cases of malignant hilar obstruction, the optimal endoscopic management regime remains controversial. In this study, we evaluated the safety and efficacy of placing a threaded stent above the sphincter of Oddi (threaded inside plastic stents, threaded PS) and compared the results with those of other stent types. Patients with malignant hilar obstruction, including those requiring biliary drainage for stent occlusion, were selected. Patients received either one of the following endoscopic indwelling stents: threaded PS, conventional plastic stents (conventional PS), or metallic stents (MS). Duration of stent patency and the incident of complication were compared in these patients. Forty-two patients underwent placement of endoscopic indwelling stents (threaded PS = 12, conventional PS = 17, MS = 13). The median duration of threaded PS patency was significantly longer than that of conventional PS patency (142 vs. 32 days; P = 0.04, logrank test). The median duration of threaded PS and MS patency was not significantly different (142 vs. 150 days, P = 0.83). Stent migration did not occur in any group. Among patients who underwent threaded PS placement as a salvage therapy after MS obstruction due to tumor ingrowth, the median duration of MS patency was significantly shorter than that of threaded PS patency (123 vs. 240 days). Threaded PS are safe and effective in cases of malignant hilar obstruction; moreover, it is a suitable therapeutic option not only for initial drainage but also for salvage therapy.

On the Convergence of Biogeography-Based Optimization for Binary Problems

Directory of Open Access Journals (Sweden)

Haiping Ma

2014-01-01

Full Text Available Biogeography-based optimization (BBO is an evolutionary algorithm inspired by biogeography, which is the study of the migration of species between habitats. A finite Markov chain model of BBO for binary problems was derived in earlier work, and some significant theoretical results were obtained. This paper analyzes the convergence properties of BBO on binary problems based on the previously derived BBO Markov chain model. Analysis reveals that BBO with only migration and mutation never converges to the global optimum. However, BBO with elitism, which maintains the best candidate in the population from one generation to the next, converges to the global optimum. In spite of previously published differences between genetic algorithms (GAs and BBO, this paper shows that the convergence properties of BBO are similar to those of the canonical GA. In addition, the convergence rate estimate of BBO with elitism is obtained in this paper and is confirmed by simulations for some simple representative problems.

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

Directory of Open Access Journals (Sweden)

Hailong Wang

2018-01-01

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

Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule

KAUST Repository

Liang, Faming; Cheng, Yichen; Lin, Guang

2014-01-01

cooling schedule, for example, a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural

Solving Bilevel Multiobjective Programming Problem by Elite Quantum Behaved Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Tao Zhang

2012-01-01

Full Text Available An elite quantum behaved particle swarm optimization (EQPSO algorithm is proposed, in which an elite strategy is exerted for the global best particle to prevent premature convergence of the swarm. The EQPSO algorithm is employed for solving bilevel multiobjective programming problem (BLMPP in this study, which has never been reported in other literatures. Finally, we use eight different test problems to measure and evaluate the proposed algorithm, including low dimension and high dimension BLMPPs, as well as attempt to solve the BLMPPs whose theoretical Pareto optimal front is not known. The experimental results show that the proposed algorithm is a feasible and efficient method for solving BLMPPs.

Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity.

Science.gov (United States)

Qi, Xin; Ju, Guohao; Xu, Shuyan

2018-04-10

The phase diversity (PD) technique needs optimization algorithms to minimize the error metric and find the global minimum. Particle swarm optimization (PSO) is very suitable for PD due to its simple structure, fast convergence, and global searching ability. However, the traditional PSO algorithm for PD still suffers from the stagnation problem (premature convergence), which can result in a wrong solution. In this paper, the stagnation problem of the traditional PSO algorithm for PD is illustrated first. Then, an explicit strategy is proposed to solve this problem, based on an in-depth understanding of the inherent optimization mechanism of the PSO algorithm. Specifically, a criterion is proposed to detect premature convergence; then a redistributing mechanism is proposed to prevent premature convergence. To improve the efficiency of this redistributing mechanism, randomized Halton sequences are further introduced to ensure the uniform distribution and randomness of the redistributed particles in the search space. Simulation results show that this strategy can effectively solve the stagnation problem of the PSO algorithm for PD, especially for large-scale and high-dimension wavefront sensing and noisy conditions. This work is further verified by an experiment. This work can improve the robustness and performance of PD wavefront sensing.

Introduction to Nonlinear and Global Optimization

NARCIS (Netherlands)

Hendrix, E.M.T.; Tóth, B.

2010-01-01

This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization

A Moiré Pattern-Based Thread Counter

Science.gov (United States)

Reich, Gary

2017-10-01

Thread count is a term used in the textile industry as a measure of how closely woven a fabric is. It is usually defined as the sum of the number of warp threads per inch (or cm) and the number of weft threads per inch. (It is sometimes confusingly described as the number of threads per square inch.) In recent years it has also become a subject of considerable interest and some controversy among consumers. Many consumers consider thread count to be a key measure of the quality or fineness of a fabric, especially bed sheets, and they seek out fabrics that advertise high counts. Manufacturers in turn have responded to this interest by offering fabrics with ever higher claimed thread counts (sold at ever higher prices), sometime achieving the higher counts by distorting the definition of the term with some "creative math." In 2005 the Federal Trade Commission noted the growing use of thread count in advertising at the retail level and warned of the potential for consumers to be misled by distortions of the definition.

Negotiation and Optimality in an Economic Model of Global Climate Change

International Nuclear Information System (INIS)

Gottinger, H.

2000-03-01

The paper addresses the problem of governmental intervention in a multi-country regime of controlling global climate change. Using a simplified case of a two-country, two-sector general equilibrium model the paper shows that the global optimal time path of economic outputs and temperature will converge to a unique steady state provided that consumers care enough about the future. To answer a set of questions relating to 'what will happen if governments decide to correct the problem of global warming?' we study the equilibrium outcome in a bargaining game where two countries negotiate an agreement on future consumption and production plans for the purpose of correcting the problem of climate change. It is shown that the agreement arising from such a negotiation process achieves the best outcome and that it can be implemented in decentralised economies by a system of taxes, subsidies and transfers. By employing the recent advances in non-cooperative bargaining theory, the agreement between two countries is derived endogenously through a well-specified bargaining procedure

Negotiation and Optimality in an Economic Model of Global Climate Change

Energy Technology Data Exchange (ETDEWEB)

Gottinger, H. [International Institute for Environmental Economics and Management IIEEM, University of Maastricht, Maastricht (Netherlands)

2000-03-01

The paper addresses the problem of governmental intervention in a multi-country regime of controlling global climate change. Using a simplified case of a two-country, two-sector general equilibrium model the paper shows that the global optimal time path of economic outputs and temperature will converge to a unique steady state provided that consumers care enough about the future. To answer a set of questions relating to 'what will happen if governments decide to correct the problem of global warming?' we study the equilibrium outcome in a bargaining game where two countries negotiate an agreement on future consumption and production plans for the purpose of correcting the problem of climate change. It is shown that the agreement arising from such a negotiation process achieves the best outcome and that it can be implemented in decentralised economies by a system of taxes, subsidies and transfers. By employing the recent advances in non-cooperative bargaining theory, the agreement between two countries is derived endogenously through a well-specified bargaining procedure.

The multi-port berth allocation problem with speed optimization and emission considerations

DEFF Research Database (Denmark)

Venturini, Giada; Iris, Cagatay; Kontovas, Christos A.

2017-01-01

The container shipping industry faces many interrelated challenges and opportunities, as its role in the global trading system has become increasingly important over the last decades. On the one side, collaboration between port terminals and shipping liners can lead to costs savings and help...... achieve a sustainable supply chain, and on the other side, the optimization of operations and sailing times leads to reductions in bunker consumption and, thus, to fuel cost and air emissions reductions. To that effect, there is an increasing need to address the integration opportunities and environmental...... issues related to container shipping through optimization. This paper focuses on the well known Berth Allocation Problem (BAP), an optimization problem assigning berthing times and positions to vessels in container terminals. We introduce a novel mathematical formulation that extends the classical BAP...

A Problem on Optimal Transportation

Science.gov (United States)

Cechlarova, Katarina

2005-01-01

Mathematical optimization problems are not typical in the classical curriculum of mathematics. In this paper we show how several generalizations of an easy problem on optimal transportation were solved by gifted secondary school pupils in a correspondence mathematical seminar, how they can be used in university courses of linear programming and…

Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization

Directory of Open Access Journals (Sweden)

Jinkui Liu

2012-01-01

Full Text Available A new nonlinear spectral conjugate descent method for solving unconstrained optimization problems is proposed on the basis of the CD method and the spectral conjugate gradient method. For any line search, the new method satisfies the sufficient descent condition gkTdk<−∥gk∥2. Moreover, we prove that the new method is globally convergent under the strong Wolfe line search. The numerical results show that the new method is more effective for the given test problems from the CUTE test problem library (Bongartz et al., 1995 in contrast to the famous CD method, FR method, and PRP method.

Stochastic and global optimization

National Research Council Canada - National Science Library

Dzemyda, Gintautas; Šaltenis, Vydūnas; Zhilinskas, A; Mockus, Jonas

2002-01-01

... and Effectiveness of Controlled Random Search E. M. T. Hendrix, P. M. Ortigosa and I. García 129 9. Discrete Backtracking Adaptive Search for Global Optimization B. P. Kristinsdottir, Z. B. Zabinsky and...

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

Global optimization of truss topology with discrete bar areas-Part II: Implementation and numerical results

DEFF Research Database (Denmark)

Achtziger, Wolfgang; Stolpe, Mathias

2009-01-01

we use the theory developed in Part I to design a convergent nonlinear branch-and-bound method tailored to solve large-scale instances of the original discrete problem. The problem formulation and the needed theoretical results from Part I are repeated such that this paper is self-contained. We focus...... the largest discrete topology design problems solved by means of global optimization....

Miguel Baraona Cockerell: The Plot and the Threads. Capitalist Modernization and the Four Spirals of Modernity. EUNA 2016

Directory of Open Access Journals (Sweden)

Lucía Rincón Soto

2017-09-01

Full Text Available This paper develops the line of thought of Miguel Baraona Cockerell, present in his book The Plot and the Threads. Capitalist Modernization and the Four Spirals of Modernity. In this book, he broadly argues that globalization, modernization, conflict and resistance are an intrinsic part of modernity. This chain of events has led to a spiral of problems which threaten the existence of mankind; problems explained in such a convincing way by the author. His criticism of the capitalist system puts in evidence the urgency for a change in mentality, a new humanism which will be implemented, as far as possible, from the confluence of social movements with a conscience leaning toward the creation of a possible world.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

Directory of Open Access Journals (Sweden)

Anjani Ragothaman

2014-01-01

Full Text Available While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Optimization and inverse problems in electromagnetism

CERN Document Server

Wiak, Sławomir

2003-01-01

From 12 to 14 September 2002, the Academy of Humanities and Economics (AHE) hosted the workshop "Optimization and Inverse Problems in Electromagnetism". After this bi-annual event, a large number of papers were assembled and combined in this book. During the workshop recent developments and applications in optimization and inverse methodologies for electromagnetic fields were discussed. The contributions selected for the present volume cover a wide spectrum of inverse and optimal electromagnetic methodologies, ranging from theoretical to practical applications. A number of new optimal and inverse methodologies were proposed. There are contributions related to dedicated software. Optimization and Inverse Problems in Electromagnetism consists of three thematic chapters, covering: -General papers (survey of specific aspects of optimization and inverse problems in electromagnetism), -Methodologies, -Industrial Applications. The book can be useful to students of electrical and electronics engineering, computer sci...

A new global particle swarm optimization for the economic emission dispatch with or without transmission losses

International Nuclear Information System (INIS)

Zou, Dexuan; Li, Steven; Li, Zongyan; Kong, Xiangyong

2017-01-01

Highlights: • A new global particle swarm optimization (NGPSO) is proposed. • NGPSO has strong convergence and desirable accuracy. • NGPSO is used to handle the economic emission dispatch with or without transmission losses. • The equality constraint can be satisfied by solving a quadratic equation. • The inequality constraints can be satisfied by using penalty function method. - Abstract: A new global particle swarm optimization (NGPSO) algorithm is proposed to solve the economic emission dispatch (EED) problems in this paper. NGPSO is different from the traditional particle swarm optimization (PSO) algorithm in two aspects. First, NGPSO uses a new position updating equation which relies on the global best particle to guide the searching activities of all particles. Second, it uses the randomization based on the uniform distribution to slightly disturb the flight trajectories of particles during the late evolutionary process. The two steps enable NGPSO to effectively execute a number of global searches, and thus they increase the chance of exploring promising solution space, and reduce the probabilities of getting trapped into local optima for all particles. On the other hand, the two objective functions of EED are normalized separately according to all candidate solutions, and then they are incorporated into one single objective function. The transformation steps are very helpful in eliminating the difference caused by the different dimensions of the two functions, and thus they strike a balance between the fuel cost and emission. In addition, a simple and common penalty function method is employed to facilitate the satisfactions of EED’s constraints. Based on these improvements in PSO, objective functions and constraints handling, high-quality solutions can be obtained for EED problems. Five examples are chosen to testify the performance of three improved PSOs on solving EED problems with or without transmission losses. Experimental results show that

Topology optimization of flow problems

DEFF Research Database (Denmark)

Gersborg, Allan Roulund

2007-01-01

This thesis investigates how to apply topology optimization using the material distribution technique to steady-state viscous incompressible flow problems. The target design applications are fluid devices that are optimized with respect to minimizing the energy loss, characteristic properties...... transport in 2D Stokes flow. Using Stokes flow limits the range of applications; nonetheless, the thesis gives a proof-of-concept for the application of the method within fluid dynamic problems and it remains of interest for the design of microfluidic devices. Furthermore, the thesis contributes...... at the Technical University of Denmark. Large topology optimization problems with 2D and 3D Stokes flow modeling are solved with direct and iterative strategies employing the parallelized Sun Performance Library and the OpenMP parallelization technique, respectively....

Topology Optimization for Convection Problems

DEFF Research Database (Denmark)

Alexandersen, Joe

2011-01-01

This report deals with the topology optimization of convection problems.That is, the aim of the project is to develop, implement and examine topology optimization of purely thermal and coupled thermomechanical problems,when the design-dependent eects of convection are taken into consideration.......This is done by the use of a self-programmed FORTRAN-code, which builds on an existing 2D-plane thermomechanical nite element code implementing during the course `41525 FEM-Heavy'. The topology optimizationfeatures have been implemented from scratch, and allows the program to optimize elastostatic mechanical...

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....

Global Optimization using Interval Analysis : Interval Optimization for Aerospace Applications

NARCIS (Netherlands)

Van Kampen, E.

2010-01-01

Optimization is an important element in aerospace related research. It is encountered for example in trajectory optimization problems, such as: satellite formation flying, spacecraft re-entry optimization and airport approach and departure optimization; in control optimization, for example in

GLOBAL OPTIMIZATION METHODS FOR GRAVITATIONAL LENS SYSTEMS WITH REGULARIZED SOURCES

International Nuclear Information System (INIS)

Rogers, Adam; Fiege, Jason D.

2012-01-01

Several approaches exist to model gravitational lens systems. In this study, we apply global optimization methods to find the optimal set of lens parameters using a genetic algorithm. We treat the full optimization procedure as a two-step process: an analytical description of the source plane intensity distribution is used to find an initial approximation to the optimal lens parameters; the second stage of the optimization uses a pixelated source plane with the semilinear method to determine an optimal source. Regularization is handled by means of an iterative method and the generalized cross validation (GCV) and unbiased predictive risk estimator (UPRE) functions that are commonly used in standard image deconvolution problems. This approach simultaneously estimates the optimal regularization parameter and the number of degrees of freedom in the source. Using the GCV and UPRE functions, we are able to justify an estimation of the number of source degrees of freedom found in previous work. We test our approach by applying our code to a subset of the lens systems included in the SLACS survey.

An Elite Decision Making Harmony Search Algorithm for Optimization Problem

Directory of Open Access Journals (Sweden)

Lipu Zhang

2012-01-01

Full Text Available This paper describes a new variant of harmony search algorithm which is inspired by a well-known item “elite decision making.” In the new algorithm, the good information captured in the current global best and the second best solutions can be well utilized to generate new solutions, following some probability rule. The generated new solution vector replaces the worst solution in the solution set, only if its fitness is better than that of the worst solution. The generating and updating steps and repeated until the near-optimal solution vector is obtained. Extensive computational comparisons are carried out by employing various standard benchmark optimization problems, including continuous design variables and integer variables minimization problems from the literature. The computational results show that the proposed new algorithm is competitive in finding solutions with the state-of-the-art harmony search variants.

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

Directory of Open Access Journals (Sweden)

Xing Liu

2014-12-01

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

Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule

KAUST Repository

Liang, Faming

2014-04-03

Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to use this much CPU time. This article proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation, it is shown that the new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, for example, a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors. Supplementary materials for this article are available online.

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-01

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization

Directory of Open Access Journals (Sweden)

Zhijun Luo

2014-01-01

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

Threaded-Field-Line Model for the Transition Region and Solar Corona

Science.gov (United States)

Sokolov, I.; van der Holst, B.; Gombosi, T. I.

2014-12-01

In numerical simulations of the solar corona, both for the ambient state and especially for dynamical processes the most computational resources are spent for maintaining the numerical solution in the Low Solar Corona and in the transition region, where the temperature gradients are very sharp and the magnetic field has a complicated topology. The degraded computational efficiency is caused by the need in a highest resolution as well as the use of the fully three-dimensional implicit solver for electron heat conduction. On the other hand, the physical nature of the processes involved is rather simple (which still does not facilitate the numerical methods) as long as the heat fluxes as well as slow plasma motional velocities are aligned with the magnetic field. The Alfven wave turbulence, which is often believed to be the main driver of the solar wind and the main source of the coronal heating, is characterized by the Poynting flux of the waves, which is also aligned with the magnetic field. Therefore, the plasma state in any point of the three-dimensional grid in the Low Solar Corona can be found by solving a set of one-dimensional equations for the magnetic field line ("thread"), which passes through this point and connects it to the chromosphere and to the global Solar Corona. In the present paper we describe an innovative computational technology based upon the use of the magnetic-field-line-threads to forlmulate the boundary condition for the global solar corona model which traces the connection of each boundary point to the cromosphere along the threads.

Global optimization of truss topology with discrete bar areas—Part I: Theory of relaxed problems

DEFF Research Database (Denmark)

Achtziger, Wolfgang; Stolpe, Mathias

2008-01-01

the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single bar area, i.e., a 0/1-problem. In contrast to heuristic methods considered in other approaches, Part I....... The main issue of the paper and of the approach lies in the fact that the relaxed nonlinear optimization problem can be formulated as a quadratic program (QP). Here the paper generalizes and extends the available theory from the literature. Although the Hessian of this QP is indefinite, it is possible...

Optically variable threads and polarization effects

Science.gov (United States)

Kretschmar, Friedrich; Burchard, Theodor; Heim, Manfred

2006-02-01

Based on common criteria for efficient security elements for banknotes the set-up of a state-of-the-art holographic security thread is described - as first representative of window embedded OVD. We continue with new colour-shifting OVD-threads - based on physical vapour deposition thin-film and liquid crystal technology. These three then form the family of optically variable threads following the same set of requirements for efficiency, durability, service to all authentication levels and economics. In addition to this set of OVD threads we introduce how liquid crystal based phase retarding layer can be used to install new authentication channels for the public use up-to machine authentication. Also we show the perspective how those development can be used to install similar sets of OVD families of foil elements on banknotes.

Preload, Coefficient of Friction, and Thread Friction in an Implant-Abutment-Screw Complex.

Science.gov (United States)

Wentaschek, Stefan; Tomalla, Sven; Schmidtmann, Irene; Lehmann, Karl Martin

To examine the screw preload, coefficient of friction (COF), and tightening torque needed to overcome the thread friction of an implant-abutment-screw complex. In a customized load frame, 25 new implant-abutment-screw complexes including uncoated titanium alloy screws were torqued and untorqued 10 times each, applying 25 Ncm. Mean preload values decreased significantly from 209.8 N to 129.5 N according to the number of repetitions. The overall COF increased correspondingly. There was no comparable trend for the thread friction component. These results suggest that the application of a used implant-abutment-screw complex may be unfavorable for obtaining optimal screw preload.

AN MHD AVALANCHE IN A MULTI-THREADED CORONAL LOOP

Energy Technology Data Exchange (ETDEWEB)

Hood, A. W.; Cargill, P. J.; Tam, K. V. [School of Mathematics and Statistics, University of St Andrews, St Andrews, Fife, KY16 9SS (United Kingdom); Browning, P. K., E-mail: awh@st-andrews.ac.uk [School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom)

2016-01-20

For the first time, we demonstrate how an MHD avalanche might occur in a multithreaded coronal loop. Considering 23 non-potential magnetic threads within a loop, we use 3D MHD simulations to show that only one thread needs to be unstable in order to start an avalanche even when the others are below marginal stability. This has significant implications for coronal heating in that it provides for energy dissipation with a trigger mechanism. The instability of the unstable thread follows the evolution determined in many earlier investigations. However, once one stable thread is disrupted, it coalesces with a neighboring thread and this process disrupts other nearby threads. Coalescence with these disrupted threads then occurs leading to the disruption of yet more threads as the avalanche develops. Magnetic energy is released in discrete bursts as the surrounding stable threads are disrupted. The volume integrated heating, as a function of time, shows short spikes suggesting that the temporal form of the heating is more like that of nanoflares than of constant heating.

Multi-thread Parallel Speech Recognition for Mobile Applications

Directory of Open Access Journals (Sweden)

LOJKA Martin

2014-05-01

Full Text Available In this paper, the server based solution of the multi-thread large vocabulary automatic speech recognition engine is described along with the Android OS and HTML5 practical application examples. The basic idea was to bring speech recognition available for full variety of applications for computers and especially for mobile devices. The speech recognition engine should be independent of commercial products and services (where the dictionary could not be modified. Using of third-party services could be also a security and privacy problem in specific applications, when the unsecured audio data could not be sent to uncontrolled environments (voice data transferred to servers around the globe. Using our experience with speech recognition applications, we have been able to construct a multi-thread speech recognition serverbased solution designed for simple applications interface (API to speech recognition engine modified to specific needs of particular application.

A global optimization method for evaporative cooling systems based on the entransy theory

International Nuclear Information System (INIS)

Yuan, Fang; Chen, Qun

2012-01-01

Evaporative cooling technique, one of the most widely used methods, is essential to both energy conservation and environment protection. This contribution introduces a global optimization method for indirect evaporative cooling systems with coupled heat and mass transfer processes based on the entransy theory to improve their energy efficiency. First, we classify the irreversible processes in the system into the heat transfer process, the coupled heat and mass transfer process and the mixing process of waters in different branches, where the irreversibility is evaluated by the entransy dissipation. Then through the total system entransy dissipation, we establish the theoretical relationship of the user demands with both the geometrical structures of each heat exchanger and the operating parameters of each fluid, and derive two optimization equation groups focusing on two typical optimization problems. Finally, an indirect evaporative cooling system is taken as an example to illustrate the applications of the newly proposed optimization method. It is concluded that there exists an optimal circulating water flow rate with the minimum total thermal conductance of the system. Furthermore, with different user demands and moist air inlet conditions, it is the global optimization, other than parametric analysis, will obtain the optimal performance of the system. -- Highlights: ► Introduce a global optimization method for evaporative cooling systems. ► Establish the direct relation between user demands and the design parameters. ► Obtain two groups of optimization equations for two typical optimization objectives. ► Solving the equations offers the optimal design parameters for the system. ► Provide the instruction for the design of coupled heat and mass transfer systems.

BRAIN Journal - Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

OpenAIRE

Ahmet Demir; Utku Kose

2016-01-01

ABSTRACT In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Sc...

Protein Structure Prediction by Protein Threading

Science.gov (United States)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

Self-adaptive global best harmony search algorithm applied to reactor core fuel management optimization

International Nuclear Information System (INIS)

Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.; Valavi, K.

2013-01-01

Highlights: • SGHS enhanced the convergence rate of LPO using some improvements in comparison to basic HS and GHS. • SGHS optimization algorithm obtained averagely better fitness relative to basic HS and GHS algorithms. • Upshot of the SGHS implementation in the LPO reveals its flexibility, efficiency and reliability. - Abstract: The aim of this work is to apply the new developed optimization algorithm, Self-adaptive Global best Harmony Search (SGHS), for PWRs fuel management optimization. SGHS algorithm has some modifications in comparison with basic Harmony Search (HS) and Global-best Harmony Search (GHS) algorithms such as dynamically change of parameters. For the demonstration of SGHS ability to find an optimal configuration of fuel assemblies, basic Harmony Search (HS) and Global-best Harmony Search (GHS) algorithms also have been developed and investigated. For this purpose, Self-adaptive Global best Harmony Search Nodal Expansion package (SGHSNE) has been developed implementing HS, GHS and SGHS optimization algorithms for the fuel management operation of nuclear reactor cores. This package uses developed average current nodal expansion code which solves the multi group diffusion equation by employment of first and second orders of Nodal Expansion Method (NEM) for two dimensional, hexagonal and rectangular geometries, respectively, by one node per a FA. Loading pattern optimization was performed using SGHSNE package for some test cases to present the SGHS algorithm capability in converging to near optimal loading pattern. Results indicate that the convergence rate and reliability of the SGHS method are quite promising and practically, SGHS improves the quality of loading pattern optimization results relative to HS and GHS algorithms. As a result, it has the potential to be used in the other nuclear engineering optimization problems

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models.

Science.gov (United States)

Pozo, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Sorribas, Albert

2011-08-25

Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Directory of Open Access Journals (Sweden)

Sorribas Albert

2011-08-01

Full Text Available Abstract Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-01-12

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

A Direct Search Algorithm for Global Optimization

Directory of Open Access Journals (Sweden)

Enrique Baeyens

2016-06-01

Full Text Available A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is differentiable and its gradient is Lipschitz continuous. The algorithm’s performance has been extensively tested using benchmark functions and compared to some well-known global optimization algorithms. The results of the computational study show that the algorithm combines both simplicity and efficiency and is competitive with the heuristics-based strategies presently used for global optimization.

Simulated Annealing-Based Krill Herd Algorithm for Global Optimization

Directory of Open Access Journals (Sweden)

Gai-Ge Wang

2013-01-01

Full Text Available Recently, Gandomi and Alavi proposed a novel swarm intelligent method, called krill herd (KH, for global optimization. To enhance the performance of the KH method, in this paper, a new improved meta-heuristic simulated annealing-based krill herd (SKH method is proposed for optimization tasks. A new krill selecting (KS operator is used to refine krill behavior when updating krill’s position so as to enhance its reliability and robustness dealing with optimization problems. The introduced KS operator involves greedy strategy and accepting few not-so-good solutions with a low probability originally used in simulated annealing (SA. In addition, a kind of elitism scheme is used to save the best individuals in the population in the process of the krill updating. The merits of these improvements are verified by fourteen standard benchmarking functions and experimental results show that, in most cases, the performance of this improved meta-heuristic SKH method is superior to, or at least highly competitive with, the standard KH and other optimization methods.

Systematic analysis of the heat exchanger arrangement problem using multi-objective genetic optimization

International Nuclear Information System (INIS)

Daróczy, László; Janiga, Gábor; Thévenin, Dominique

2014-01-01

A two-dimensional cross-flow tube bank heat exchanger arrangement problem with internal laminar flow is considered in this work. The objective is to optimize the arrangement of tubes and find the most favorable geometries, in order to simultaneously maximize the rate of heat exchange while obtaining a minimum pressure loss. A systematic study was performed involving a large number of simulations. The global optimization method NSGA-II was retained. A fully automatized in-house optimization environment was used to solve the problem, including mesh generation and CFD (computational fluid dynamics) simulations. The optimization was performed in parallel on a Linux cluster with a very good speed-up. The main purpose of this article is to illustrate and analyze a heat exchanger arrangement problem in its most general form and to provide a fundamental understanding of the structure of the Pareto front and optimal geometries. The considered conditions are particularly suited for low-power applications, as found in a growing number of practical systems in an effort toward increasing energy efficiency. For such a detailed analysis with more than 140 000 CFD-based evaluations, a design-of-experiment study involving a response surface would not be sufficient. Instead, all evaluations rely on a direct solution using a CFD solver. - Highlights: • Cross-flow tube bank heat exchanger arrangement problem. • A fully automatized multi-objective optimization based on genetic algorithm. • A systematic study involving a large number of CFD (computational fluid dynamics) simulations

Threaded cognition : An integrated theory of concurrent multitasking

NARCIS (Netherlands)

Salvucci, Dario D.; Taatgen, Niels A.

The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking-that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed

Determination of the Tapping Part Diameter of the Thread Mill

Directory of Open Access Journals (Sweden)

A. E. Dreval'

2015-01-01

Full Text Available Currently, there is a tendency to increase the proportion of thread milling operations, among other ways of tapping, which is associated with increasing number of CNC machines, flexibility and versatility of the process.Developments presently existing in the RF and used in the thread mills deal, mainly, with the thread milling cutter designs, to process internal and external thread with straight flutes made from high-speed steel.The paper presents a technique to calculate and select the initial design parameters, i.e. the external diameter of the tapping part of thread milling cutter, which is chosen as a basic computational design. The analysis of directories of tool companies containing foreign de-signs of solid thread end-milling cutters has shown that most of them rep-resent the thread cutter designs made of solid carbide. There are solid and interlocking side milling cutters, which use a tapping part both as a single-disk and as a multi-disk one; chip flutes are made to be both as direct and as screw; solid designs of cutters are made from carbide with a diameter of up to 20 ... 25 mm; thread cutters can be left- and right-hand cutting; Designs of the combined thread mills are proposed; internal channels are used for coolant supply.It is shown that the purpose of the external diameter of the tapping part of the thread mill should take into account the effect of the thread mill diameter on the milling process performance, precision of thread profile received, taper thread, tool strength, and the volume of flutes.The analysis has shown that when choosing the external diameter of the thread mill it worth taking its maximum diameter to improve the char-acteristics of the process under the restrictions imposed on the accuracy of the formed thread.

A Mathematical Optimization Problem in Bioinformatics

Science.gov (United States)

Heyer, Laurie J.

2008-01-01

This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…

Problems of radiation protection optimization

International Nuclear Information System (INIS)

Morkunas, G.

2003-01-01

One of the basic principles - optimization of radiation protection - is rather well understood by everybody engaged in protection of humans from ionizing radiation. However, the practical application of this principle is very problematic. This fact can be explained by vagueness of concept of dose constraints, possible legal consequences of any decision based on this principle, traditions of prescriptive system of radiation protection requirements in some countries, insufficiency of qualified expertise. The examples of optimization problems are the different attention given to different kinds of practices, not optimized application of remedial measures, strict requirements for radioactive contamination of imported products, uncertainties in optimization in medical applications of ionizing radiation. Such tools as international co-operation including regional networks of information exchange, training of qualified experts, identification of measurable indicators used for judging about the level of optimization may be the helpful practical means in solving of these problems. It is evident that the principle of optimization can not be replaced by any other alternative despite its complexity. The means for its practical implementation shall be searched for. (author)

Annealing evolutionary stochastic approximation Monte Carlo for global optimization

KAUST Repository

Liang, Faming

2010-04-08

In this paper, we propose a new algorithm, the so-called annealing evolutionary stochastic approximation Monte Carlo (AESAMC) algorithm as a general optimization technique, and study its convergence. AESAMC possesses a self-adjusting mechanism, whose target distribution can be adapted at each iteration according to the current samples. Thus, AESAMC falls into the class of adaptive Monte Carlo methods. This mechanism also makes AESAMC less trapped by local energy minima than nonadaptive MCMC algorithms. Under mild conditions, we show that AESAMC can converge weakly toward a neighboring set of global minima in the space of energy. AESAMC is tested on multiple optimization problems. The numerical results indicate that AESAMC can potentially outperform simulated annealing, the genetic algorithm, annealing stochastic approximation Monte Carlo, and some other metaheuristics in function optimization. © 2010 Springer Science+Business Media, LLC.

Microwave tomography global optimization, parallelization and performance evaluation

CERN Document Server

Noghanian, Sima; Desell, Travis; Ashtari, Ali

2014-01-01

This book provides a detailed overview on the use of global optimization and parallel computing in microwave tomography techniques. The book focuses on techniques that are based on global optimization and electromagnetic numerical methods. The authors provide parallelization techniques on homogeneous and heterogeneous computing architectures on high performance and general purpose futuristic computers. The book also discusses the multi-level optimization technique, hybrid genetic algorithm and its application in breast cancer imaging.

Evaluating the use of laser radiation in cleaning of copper embroidery threads on archaeological Egyptian textiles

International Nuclear Information System (INIS)

Abdel-Kareem, Omar; Harith, M.A.

2008-01-01

Cleaning of copper embroidery threads on archaeological textiles is still a complicated conservation process, as most textile conservators believe that the advantages of using traditional cleaning techniques are less than their disadvantages. In this study, the uses of laser cleaning method and two modified recipes of wet cleaning methods were evaluated for cleaning of the corroded archaeological Egyptian copper embroidery threads on an archaeological Egyptian textile fabric. Some corroded copper thread samples were cleaned using modified recipes of wet cleaning method; other corroded copper thread samples were cleaned with Q-switched Nd:YAG laser radiation of wavelength 532 nm. All tested metal thread samples before and after cleaning were investigated using a light microscope and a scanning electron microscope with an energy dispersive X-ray analysis unit. Also the laser-induced breakdown spectroscopy (LIBS) technique was used for the elemental analysis of laser-cleaned samples to follow up the laser cleaning procedure. The results show that laser cleaning is the most effective method among all tested methods in the cleaning of corroded copper threads. It can be used safely in removing the corrosion products without any damage to both metal strips and fibrous core. The tested laser cleaning technique has solved the problems caused by other traditional cleaning techniques that are commonly used in the cleaning of metal threads on museum textiles

Evaluating the use of laser radiation in cleaning of copper embroidery threads on archaeological Egyptian textiles

Energy Technology Data Exchange (ETDEWEB)

Abdel-Kareem, Omar [Conservation Department, Faculty of Archaeology, Cairo University, El-Gamaa Street, El-Giza (Egypt)], E-mail: Omaa67@yahoo.com; Harith, M.A. [National Institute of Laser Enhanced Science, Cairo University (Egypt)], E-mail: mharithm@niles.edu.eg

2008-07-15

Cleaning of copper embroidery threads on archaeological textiles is still a complicated conservation process, as most textile conservators believe that the advantages of using traditional cleaning techniques are less than their disadvantages. In this study, the uses of laser cleaning method and two modified recipes of wet cleaning methods were evaluated for cleaning of the corroded archaeological Egyptian copper embroidery threads on an archaeological Egyptian textile fabric. Some corroded copper thread samples were cleaned using modified recipes of wet cleaning method; other corroded copper thread samples were cleaned with Q-switched Nd:YAG laser radiation of wavelength 532 nm. All tested metal thread samples before and after cleaning were investigated using a light microscope and a scanning electron microscope with an energy dispersive X-ray analysis unit. Also the laser-induced breakdown spectroscopy (LIBS) technique was used for the elemental analysis of laser-cleaned samples to follow up the laser cleaning procedure. The results show that laser cleaning is the most effective method among all tested methods in the cleaning of corroded copper threads. It can be used safely in removing the corrosion products without any damage to both metal strips and fibrous core. The tested laser cleaning technique has solved the problems caused by other traditional cleaning techniques that are commonly used in the cleaning of metal threads on museum textiles.

Evaluating the use of laser radiation in cleaning of copper embroidery threads on archaeological Egyptian textiles

Science.gov (United States)

Abdel-Kareem, Omar; Harith, M. A.

2008-07-01

Cleaning of copper embroidery threads on archaeological textiles is still a complicated conservation process, as most textile conservators believe that the advantages of using traditional cleaning techniques are less than their disadvantages. In this study, the uses of laser cleaning method and two modified recipes of wet cleaning methods were evaluated for cleaning of the corroded archaeological Egyptian copper embroidery threads on an archaeological Egyptian textile fabric. Some corroded copper thread samples were cleaned using modified recipes of wet cleaning method; other corroded copper thread samples were cleaned with Q-switched Nd:YAG laser radiation of wavelength 532 nm. All tested metal thread samples before and after cleaning were investigated using a light microscope and a scanning electron microscope with an energy dispersive X-ray analysis unit. Also the laser-induced breakdown spectroscopy (LIBS) technique was used for the elemental analysis of laser-cleaned samples to follow up the laser cleaning procedure. The results show that laser cleaning is the most effective method among all tested methods in the cleaning of corroded copper threads. It can be used safely in removing the corrosion products without any damage to both metal strips and fibrous core. The tested laser cleaning technique has solved the problems caused by other traditional cleaning techniques that are commonly used in the cleaning of metal threads on museum textiles.

A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

Directory of Open Access Journals (Sweden)

Muhammad Farhan Ausaf

2015-12-01

Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Evans BAIDOO

2017-03-01

Full Text Available Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.

The global warming problem

International Nuclear Information System (INIS)

Anon.

1990-01-01

In this chapter, a discussion is presented of the global warming problem and activities contributing to the formation of acid rain, urban smog and to the depletion of the ozone layer. Globally, about two-thirds of anthropogenic carbon dioxide emissions arise from fossil-fuel burning; the rest arise primarily from deforestation. Chlorofluorocarbons are the second largest contributor to global warming, accounting for about 20% of the total. The third largest contributor is methane, followed by ozone and nitrous oxide. A study of current activities in the US that contribute to global warming shows the following: electric power plants account for about 33% of carbon dioxide emissions; motor vehicles, planes and ships (31%); industrial plants (24%); commercial and residential buildings (11%)

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

Threaded Cognition: An Integrated Theory of Concurrent Multitasking

Science.gov (United States)

Salvucci, Dario D.; Taatgen, Niels A.

2008-01-01

The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking--that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed across other available resources (e.g., perceptual…

Adjoint-based global variance reduction approach for reactor analysis problems

International Nuclear Information System (INIS)

Zhang, Qiong; Abdel-Khalik, Hany S.

2011-01-01

A new variant of a hybrid Monte Carlo-Deterministic approach for simulating particle transport problems is presented and compared to the SCALE FW-CADIS approach. The new approach, denoted by the Subspace approach, optimizes the selection of the weight windows for reactor analysis problems where detailed properties of all fuel assemblies are required everywhere in the reactor core. Like the FW-CADIS approach, the Subspace approach utilizes importance maps obtained from deterministic adjoint models to derive automatic weight-window biasing. In contrast to FW-CADIS, the Subspace approach identifies the correlations between weight window maps to minimize the computational time required for global variance reduction, i.e., when the solution is required everywhere in the phase space. The correlations are employed to reduce the number of maps required to achieve the same level of variance reduction that would be obtained with single-response maps. Numerical experiments, serving as proof of principle, are presented to compare the Subspace and FW-CADIS approaches in terms of the global reduction in standard deviation. (author)

Global optimization for motion estimation with applications to ultrasound videos of carotid artery plaques

Science.gov (United States)

Murillo, Sergio; Pattichis, Marios; Soliz, Peter; Barriga, Simon; Loizou, C. P.; Pattichis, C. S.

2010-03-01

Motion estimation from digital video is an ill-posed problem that requires a regularization approach. Regularization introduces a smoothness constraint that can reduce the resolution of the velocity estimates. The problem is further complicated for ultrasound videos (US), where speckle noise levels can be significant. Motion estimation using optical flow models requires the modification of several parameters to satisfy the optical flow constraint as well as the level of imposed smoothness. Furthermore, except in simulations or mostly unrealistic cases, there is no ground truth to use for validating the velocity estimates. This problem is present in all real video sequences that are used as input to motion estimation algorithms. It is also an open problem in biomedical applications like motion analysis of US of carotid artery (CA) plaques. In this paper, we study the problem of obtaining reliable ultrasound video motion estimates for atherosclerotic plaques for use in clinical diagnosis. A global optimization framework for motion parameter optimization is presented. This framework uses actual carotid artery motions to provide optimal parameter values for a variety of motions and is tested on ten different US videos using two different motion estimation techniques.

Topology optimization of wave-propagation problems

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard; Sigmund, Ole

2006-01-01

Topology optimization is demonstrated as a useful tool for systematic design of wave-propagation problems. We illustrate the applicability of the method for optical, acoustic and elastic devices and structures.......Topology optimization is demonstrated as a useful tool for systematic design of wave-propagation problems. We illustrate the applicability of the method for optical, acoustic and elastic devices and structures....

Infinite-horizon optimal control problems in economics

International Nuclear Information System (INIS)

Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V

2012-01-01

This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.

Optimality conditions for the numerical solution of optimization problems with PDE constraints :

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro; Ridzal, Denis

2014-03-01

A theoretical framework for the numerical solution of partial di erential equation (PDE) constrained optimization problems is presented in this report. This theoretical framework embodies the fundamental infrastructure required to e ciently implement and solve this class of problems. Detail derivations of the optimality conditions required to accurately solve several parameter identi cation and optimal control problems are also provided in this report. This will allow the reader to further understand how the theoretical abstraction presented in this report translates to the application.

Effect of thread embedding acupuncture for facial wrinkles and laxity: a single-arm, prospective, open-label study

Directory of Open Access Journals (Sweden)

Younghee Yun

2017-12-01

Full Text Available Background: There is a growing trend for patients to seek the least invasive treatments with less risk of complications and downtime for facial rejuvenation. Thread embedding acupuncture has become popular as a minimally invasive treatment. However, there is little clinical evidence in the literature regarding its effects. Methods: This single-arm, prospective, open-label study recruited participants who were women aged 40–59 years, with Glogau photoaging scale III–IV. Fourteen participants received thread embedding acupuncture one time and were measured before and after 1 week from the procedure. The primary outcome was a jowl to subnasale vertical distance. The secondary outcomes were facial wrinkle distances, global esthetic improvement scale, Alexiades–Armenakas laxity scale, and patient-oriented self-assessment scale. Results: Fourteen participants underwent thread embedding acupuncture alone, and 12 participants revisited for follow-up outcome measures. For the primary outcome measure, both jowls were elevated in vertical height by 1.87 mm (left and 1.43 mm (right. Distances of both melolabial and nasolabial folds showed significant improvement. In the Alexiades–Armenakas laxity scale, each evaluator evaluated for four and nine participants by 0.5 grades improved. In the global aesthetic improvement scale, improvement was graded as 1 and 2 in nine and five cases, respectively. The most common adverse events were mild bruising, swelling, and pain. However, adverse events occurred, although mostly minor and of short duration. Conclusion: In this study, thread embedding acupuncture showed clinical potential for facial wrinkles and laxity. However, further large-scale trials with a controlled design and objective measurements are needed. Keywords: polydioxanone, rejuvenation, rhytidoplasty, skin aging, thread embedding acupuncture

Optimal recombination in genetic algorithms for combinatorial optimization problems: Part I

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2014-01-01

Full Text Available This paper surveys results on complexity of the optimal recombination problem (ORP, which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We consider efficient reductions of the ORPs, allowing to establish polynomial solvability or NP-hardness of the ORPs, as well as direct proofs of hardness results. Part I presents the basic principles of optimal recombination with a survey of results on Boolean Linear Programming Problems. Part II (to appear in a subsequent issue is devoted to the ORPs for problems which are naturally formulated in terms of search for an optimal permutation.

Thread-Skip: An Undefined Common Observation.

Science.gov (United States)

McDermott, Peter; Allan, William DE

When a screw-retained implant prosthesis is removed, a click is heard and a slight axial shift is felt, indicating the screw has been fully removed from the retaining thread. This common observation has never been described in the literature. This article describes the click, and it is proposed it be termed thread-skip.

Approximative solutions of stochastic optimization problem

Czech Academy of Sciences Publication Activity Database

Lachout, Petr

2010-01-01

Roč. 46, č. 3 (2010), s. 513-523 ISSN 0023-5954 R&D Projects: GA ČR GA201/08/0539 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic optimization problem * sensitivity * approximative solution Subject RIV: BA - General Mathematics Impact factor: 0.461, year: 2010 http://library.utia.cas.cz/separaty/2010/SI/lachout-approximative solutions of stochastic optimization problem.pdf

CPC: programming with a massive number of lightweight threads

OpenAIRE

Kerneis, Gabriel; Chroboczek, Juliusz

2011-01-01

To appear in PLACES'11.; International audience; Threads are a convenient and modular abstraction for writing concurrent programs, but often fairly expensive. The standard alternative to threads, event-loop programming, allows much lighter units of concurrency, but leads to code that is difficult to write and even harder to understand. Continuation Passing C (CPC) is a translator that converts a program written in threaded style into a program written with events and native system threads, at...

Infinite-horizon optimal control problems in economics

Energy Technology Data Exchange (ETDEWEB)

Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V

2012-04-30

This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

Science.gov (United States)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto

Communication Optimizations for Fine-Grained UPCApplications

Energy Technology Data Exchange (ETDEWEB)

Chen, Wei-Yu; Iancu, Costin; Yelick, Katherine

2005-07-08

Global address space languages like UPC exhibit high performance and portability on a broad class of shared and distributed memory parallel architectures. The most scalable applications use bulk memory copies rather than individual reads and writes to the shared space, but finer-grained sharing can be useful for scenarios such as dynamic load balancing, event signaling, and distributed hash tables. In this paper we present three optimization techniques for global address space programs with fine-grained communication: redundancy elimination, use of split-phase communication, and communication coalescing. Parallel UPC programs are analyzed using static single assignment form and a data flow graph, which are extended to handle the various shared and private pointer types that are available in UPC. The optimizations also take advantage of UPC's relaxed memory consistency model, which reduces the need for cross thread analysis. We demonstrate the effectiveness of the analysis and optimizations using several benchmarks, which were chosen to reflect the kinds of fine-grained, communication-intensive phases that exist in some larger applications. The optimizations show speedups of up to 70 percent on three parallel systems, which represent three different types of cluster network technologies.

Cuckoo search with Lévy flights for weighted Bayesian energy functional optimization in global-support curve data fitting.

Science.gov (United States)

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems.

Science.gov (United States)

Wang, Handing; Jin, Yaochu; Doherty, John

2017-09-01

Function evaluations (FEs) of many real-world optimization problems are time or resource consuming, posing a serious challenge to the application of evolutionary algorithms (EAs) to solve these problems. To address this challenge, the research on surrogate-assisted EAs has attracted increasing attention from both academia and industry over the past decades. However, most existing surrogate-assisted EAs (SAEAs) either still require thousands of expensive FEs to obtain acceptable solutions, or are only applied to very low-dimensional problems. In this paper, a novel surrogate-assisted particle swarm optimization (PSO) inspired from committee-based active learning (CAL) is proposed. In the proposed algorithm, a global model management strategy inspired from CAL is developed, which searches for the best and most uncertain solutions according to a surrogate ensemble using a PSO algorithm and evaluates these solutions using the expensive objective function. In addition, a local surrogate model is built around the best solution obtained so far. Then, a PSO algorithm searches on the local surrogate to find its optimum and evaluates it. The evolutionary search using the global model management strategy switches to the local search once no further improvement can be observed, and vice versa. This iterative search process continues until the computational budget is exhausted. Experimental results comparing the proposed algorithm with a few state-of-the-art SAEAs on both benchmark problems up to 30 decision variables as well as an airfoil design problem demonstrate that the proposed algorithm is able to achieve better or competitive solutions with a limited budget of hundreds of exact FEs.

Optimization strategies for discrete multi-material stiffness optimization

DEFF Research Database (Denmark)

Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias

2011-01-01

Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....

Outcomes of polydioxanone knotless thread lifting for facial rejuvenation.

Science.gov (United States)

Suh, Dong Hye; Jang, Hee Won; Lee, Sang Jun; Lee, Won Seok; Ryu, Hwa Jung

2015-06-01

Thread lifting is a minimally invasive technique for facial rejuvenation. Various devices for thread lifting using polydioxanone (PDO) are popular in aesthetic clinics in Korea, but there have been a few studies regarding its use. To describe PDO thread and techniques adopted to counteract the descent and laxity of the face. A retrospective chart review was conducted over a 24-month period. A total of 31 thread lifting procedures were performed. On each side, 5 bidirectional cog threads were used in the procedure for the flabby skin of the nasolabial folds. And, the procedure was performed on the marionette line using 2 twin threads. In most patients (87%), the results obtained were considered satisfactory. Consensus ratings by 2 physicians found that objective outcomes were divided among "excellent," "good," "fair," and "poor." Texture wise, the outcome ratings were 13 as excellent and 9 as good. Lifting wise, ratings were 11 as excellent and 6 as good. The incidence of complications was low and not serious. Facial rejuvenation using PDO thread is a safe and effective procedure associated with only minor complications when performed on patients with modest face sagging, fine wrinkles, and marked facial pores.

Topology optimization for acoustic-structure interaction problems

DEFF Research Database (Denmark)

Yoon, Gil Ho; Jensen, Jakob Søndergaard; Sigmund, Ole

2006-01-01

We propose a gradient based topology optimization algorithm for acoustic-structure (vibro-acoustic) interaction problems without an explicit interfacing boundary representation. In acoustic-structure interaction problems, the pressure field and the displacement field are governed by the Helmholtz...... to subdomain interfaces evolving during the optimization process. In this paper, we propose to use a mixed finite element formulation with displacements and pressure as primary variables (u/p formulation) which eliminates the need for explicit boundary representation. In order to describe the Helmholtz......-dimensional acoustic-structure interaction problems are optimized to show the validity of the proposed method....

Arsenic contamination in food chain: Thread to food security

Science.gov (United States)

Shekhar Azad Kashyap, Chandra; Singh, Swati

2017-04-01

The supply of good quality food is a necessity for economic and social health welfare of urban and rural population. Over the last several decades groundwater contamination in developing countries has assumed dangerous levels as a result millions of people are at risk. This is so particularly with respect to arsenic that has registered high concentration in groundwater in countries like India and Bangladesh. The arsenic content in groundwater varies from 10 to 780 µg/L, which is far above the levels for drinking water standards prescribed by World Health Organization (WHO). Currently arsenic has entered in food chain due to irrigation with arsenic contaminated water. In the present study reports the arsenic contamination in groundwater that is being used for irrigating paddy in Manipur and West Bengal. The arsenic content in irrigation water is 475 µg/L and 780 µg/L in Manipur and West Bengal, respectively. In order to assess the effect of such waters on the rice crop, we collected rice plant from Manipur and determined the arsenic content in roots, stem, and grain. The arsenic content in grain varies from 110 to 190 mg/kg while the limit of arsenic intake by humans is 10 mg/kg (WHO). This problem is not confine to the area, it spread global level, and rice being cultivated in these regions is export to the other countries like USA, Middle East and Europe and will be thread to global food security.

Thread-level parallelization and optimization of NWChem for the Intel MIC architecture

Energy Technology Data Exchange (ETDEWEB)

Shan, Hongzhang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); de Jong, Wibe [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-01-01

In the multicore era it was possible to exploit the increase in on-chip parallelism by simply running multiple MPI processes per chip. Unfortunately, manycore processors' greatly increased thread- and data-level parallelism coupled with a reduced memory capacity demand an altogether different approach. In this paper we explore augmenting two NWChem modules, triples correction of the CCSD(T) and Fock matrix construction, with OpenMP in order that they might run efficiently on future manycore architectures. As the next NERSC machine will be a self-hosted Intel MIC (Xeon Phi) based supercomputer, we leverage an existing MIC testbed at NERSC to evaluate our experiments. In order to proxy the fact that future MIC machines will not have a host processor, we run all of our experiments in native mode. We found that while straightforward application of OpenMP to the deep loop nests associated with the tensor contractions of CCSD(T) was sufficient in attaining high performance, significant e ort was required to safely and efeciently thread the TEXAS integral package when constructing the Fock matrix. Ultimately, our new MPI+OpenMP hybrid implementations attain up to 65× better performance for the triples part of the CCSD(T) due in large part to the fact that the limited on-card memory limits the existing MPI implementation to a single process per card. Additionally, we obtain up to 1.6× better performance on Fock matrix constructions when compared with the best MPI implementations running multiple processes per card.

Thread-Level Parallelization and Optimization of NWChem for the Intel MIC Architecture

Energy Technology Data Exchange (ETDEWEB)

Shan, Hongzhang; Williams, Samuel; Jong, Wibe de; Oliker, Leonid

2014-10-10

In the multicore era it was possible to exploit the increase in on-chip parallelism by simply running multiple MPI processes per chip. Unfortunately, manycore processors' greatly increased thread- and data-level parallelism coupled with a reduced memory capacity demand an altogether different approach. In this paper we explore augmenting two NWChem modules, triples correction of the CCSD(T) and Fock matrix construction, with OpenMP in order that they might run efficiently on future manycore architectures. As the next NERSC machine will be a self-hosted Intel MIC (Xeon Phi) based supercomputer, we leverage an existing MIC testbed at NERSC to evaluate our experiments. In order to proxy the fact that future MIC machines will not have a host processor, we run all of our experiments in tt native mode. We found that while straightforward application of OpenMP to the deep loop nests associated with the tensor contractions of CCSD(T) was sufficient in attaining high performance, significant effort was required to safely and efficiently thread the TEXAS integral package when constructing the Fock matrix. Ultimately, our new MPI OpenMP hybrid implementations attain up to 65x better performance for the triples part of the CCSD(T) due in large part to the fact that the limited on-card memory limits the existing MPI implementation to a single process per card. Additionally, we obtain up to 1.6x better performance on Fock matrix constructions when compared with the best MPI implementations running multiple processes per card.

Adaptive extremal optimization by detrended fluctuation analysis

International Nuclear Information System (INIS)

Hamacher, K.

2007-01-01

Global optimization is one of the key challenges in computational physics as several problems, e.g. protein structure prediction, the low-energy landscape of atomic clusters, detection of community structures in networks, or model-parameter fitting can be formulated as global optimization problems. Extremal optimization (EO) has become in recent years one particular, successful approach to the global optimization problem. As with almost all other global optimization approaches, EO is driven by an internal dynamics that depends crucially on one or more parameters. Recently, the existence of an optimal scheme for this internal parameter of EO was proven, so as to maximize the performance of the algorithm. However, this proof was not constructive, that is, one cannot use it to deduce the optimal parameter itself a priori. In this study we analyze the dynamics of EO for a test problem (spin glasses). Based on the results we propose an online measure of the performance of EO and a way to use this insight to reformulate the EO algorithm in order to construct optimal values of the internal parameter online without any input by the user. This approach will ultimately allow us to make EO parameter free and thus its application in general global optimization problems much more efficient

Double-Twisted Conductive Smart Threads Comprising a Homogeneously and a Gradient-Coated Thread for Multidimensional Flexible Pressure-Sensing Devices

KAUST Repository

Tai, Yanlong

2016-03-17

Fiber-based, flexible pressure-sensing systems have attracted attention recently due to their promising application as electronic skins. Here, a new kind of flexible pressure-sensing device based on a polydimethylsiloxane membrane instrumented with double-twisted smart threads (DTSTs) is reported. DTSTs are made of two conductive threads obtained by coating cotton threads with carbon nanotubes. One thread is coated with a homogeneous thickness of single-walled carbon nanotubes (SWCNTs) to detect the intensity of an applied load and the other is coated with a graded thickness of SWCNTs to identify the position of the load along the thread. The mechanism and capacity of DTSTs to accurately sense an applied load are systematically analyzed. Results demonstrate that the fabricated 1D, 2D, and 3D sensing devices can be used to predict both the intensity and the position of an applied load. The sensors feature high sensitivity (between ≈0.1% and 1.56% kPa) and tunable resolution, good cycling resilience (>104 cycles), and a short response time (minimum 2.5 Hz). The presented strategy is a viable alternative for the design of simple, low-cost pressure sensors.

Fabrication and Characterisation of Flexible Coaxial Thin Thread Supercapacitors

Directory of Open Access Journals (Sweden)

Fulian Qiu

2014-08-01

Full Text Available Flexible coaxial thin thread supercapacitors were fabricated semi-automatically using a dip coating method. A typical coaxial thin thread supercapacitor of a length of 70 cm demonstrated a specific length capacitance of 0.3 mF cm-1 (11.2 mF cm-2 and 2.18 F cm-3 at 5 mV s-1, the device exhibited good electrochemical performance with a high volume energy density of 0.22 mWh cm-3 at a power density of 22 mW cm-3. Thread supercapacitors were assembled in series and parallel combinations, the accepted models for series and parallel circuit combinations were obeyed for two coaxial thread supercapacitors. The thread shows high flexibility and uniformity of specific length capacitance, one integrated with a commercial solar cell could be charged and power a LED. The process is simple, robust and easy to scale up to make unlimited length thread supercapacitors for numerous miniaturized and flexible electronic applications.

A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

Directory of Open Access Journals (Sweden)

Weitian Lin

2014-01-01

Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

Well-posed optimization problems

CERN Document Server

Dontchev, Asen L

1993-01-01

This book presents in a unified way the mathematical theory of well-posedness in optimization. The basic concepts of well-posedness and the links among them are studied, in particular Hadamard and Tykhonov well-posedness. Abstract optimization problems as well as applications to optimal control, calculus of variations and mathematical programming are considered. Both the pure and applied side of these topics are presented. The main subject is often introduced by heuristics, particular cases and examples. Complete proofs are provided. The expected knowledge of the reader does not extend beyond textbook (real and functional) analysis, some topology and differential equations and basic optimization. References are provided for more advanced topics. The book is addressed to mathematicians interested in optimization and related topics, and also to engineers, control theorists, economists and applied scientists who can find here a mathematical justification of practical procedures they encounter.

On the complexity of determining tolerances for ->e--optimal solutions to min-max combinatorial optimization problems

NARCIS (Netherlands)

Ghosh, D.; Sierksma, G.

2000-01-01

Sensitivity analysis of e-optimal solutions is the problem of calculating the range within which a problem parameter may lie so that the given solution re-mains e-optimal. In this paper we study the sensitivity analysis problem for e-optimal solutions tocombinatorial optimization problems with

Finding Multiple Optimal Solutions to Optimal Load Distribution Problem in Hydropower Plant

Directory of Open Access Journals (Sweden)

Xinhao Jiang

2012-05-01

Full Text Available Optimal load distribution (OLD among generator units of a hydropower plant is a vital task for hydropower generation scheduling and management. Traditional optimization methods for solving this problem focus on finding a single optimal solution. However, many practical constraints on hydropower plant operation are very difficult, if not impossible, to be modeled, and the optimal solution found by those models might be of limited practical uses. This motivates us to find multiple optimal solutions to the OLD problem, which can provide more flexible choices for decision-making. Based on a special dynamic programming model, we use a modified shortest path algorithm to produce multiple solutions to the problem. It is shown that multiple optimal solutions exist for the case study of China’s Geheyan hydropower plant, and they are valuable for assessing the stability of generator units, showing the potential of reducing occurrence times of units across vibration areas.

New compilers speed up applications for Intel-based systems; Intel Compilers pave the way for Intel's Hyper-threading technology

CERN Multimedia

2002-01-01

"Intel Corporation today introduced updated tools to help software developers optimize applications for Intel's expanding family of architectures with key innovations such as Intel's Hyper Threading Technology (1 page).

Visual thread quality for precision miniature mechanisms

Energy Technology Data Exchange (ETDEWEB)

Gillespie, L.K.

1981-04-01

Threaded features have eight visual appearance factors which can affect their function in precision miniature mechanisms. The Bendix practice in deburring, finishing, and accepting these conditions on miniature threads is described as is their impact in assemblies of precision miniature electromechanical assemblies.

A multi-threading approach to secure VERIFYPIN

CSIR Research Space (South Africa)

Frieslaar, Ibraheem

2016-10-01

Full Text Available along side a pin-acceptance program in a multi-threaded environment. These threads are inserted randomly on each execution of the program to create confusion for the attacker. Moreover, the research proposes a more improved version of the pin...

Global stability, periodic solutions, and optimal control in a nonlinear differential delay model

Directory of Open Access Journals (Sweden)

Anatoli F. Ivanov

2010-09-01

Full Text Available A nonlinear differential equation with delay serving as a mathematical model of several applied problems is considered. Sufficient conditions for the global asymptotic stability and for the existence of periodic solutions are given. Two particular applications are treated in detail. The first one is a blood cell production model by Mackey, for which new periodicity criteria are derived. The second application is a modified economic model with delay due to Ramsey. An optimization problem for a maximal consumption is stated and solved for the latter.

Firefly Mating Algorithm for Continuous Optimization Problems

Directory of Open Access Journals (Sweden)

Amarita Ritthipakdee

2017-01-01

Full Text Available This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA, for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i the mutual attraction between males and females causes them to mate and (ii fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.

Introduction to global energetic problems

International Nuclear Information System (INIS)

Gicquel, R.

1992-01-01

This book gives a view on global energetic problems and proposes a thorough economic analysis on principle aspects taken into account: energy supply, depending energy sources and available technologic channels, relationships between macro-economy and energy demand, new size of energy problems (environmental effects, overcosts of renewable energy sources, necessity of an high technologic development...). 38 refs

SOCP relaxation bounds for the optimal subset selection problem applied to robust linear regression

OpenAIRE

Flores, Salvador

2015-01-01

This paper deals with the problem of finding the globally optimal subset of h elements from a larger set of n elements in d space dimensions so as to minimize a quadratic criterion, with an special emphasis on applications to computing the Least Trimmed Squares Estimator (LTSE) for robust regression. The computation of the LTSE is a challenging subset selection problem involving a nonlinear program with continuous and binary variables, linked in a highly nonlinear fashion. The selection of a ...

Radiometric determination of uniformity of putting paraffin on textile threads

International Nuclear Information System (INIS)

Ridel', Z.; Kherrmann, Eh.; Shefer, I.; Tseiner, A.

1979-01-01

To improve processing of the natural and synthetic fiber threads on stocking-frames, they are treated by paraffin. Paraffin is applied in the amounts nearly equal to 0.1 -1.0 g for 10 4 m of the thread's length. To determine amount of paraffin on thread and to determine uniformity if its application, a radiometric method has been developed. As a radioactive label, didocilephosphate of rare earths was used. This compound has good solubility in hydrocarbons and does not change physical properties of paraffin in the investigated field of its application as well as its concentration. It is possible to add to paraffin this radioactive label or a non-active label with subsequent its activation. Amount of paraffin, applied on a thread is determined by means of measurement of activity of thread samples of different length. Information about uniformity of paraffin application on thread have been obtained by means of autoradiography. It has been found that paraffin in mainly applied on the thread's bulges [ru

The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems

Science.gov (United States)

Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860

Gold thread implantation promotes hair growth in human and mice

Science.gov (United States)

Kim, Jong-Hwan; Cho, Eun-Young; Kwon, Euna; Kim, Woo-Ho; Park, Jin-Sung; Lee, Yong-Soon

2017-01-01

Thread-embedding therapy has been widely applied for cosmetic purposes such as wrinkle reduction and skin tightening. Particularly, gold thread was reported to support connective tissue regeneration, but, its role in hair biology remains largely unknown due to lack of investigation. When we implanted gold thread and Happy Lift™ in human patient for facial lifting, we unexpectedly found an increase of hair regrowth in spite of no use of hair growth medications. When embedded into the depilated dorsal skin of mice, gold thread or polyglycolic acid (PGA) thread, similarly to 5% minoxidil, significantly increased the number of hair follicles on day 14 after implantation. And, hair re-growth promotion in the gold threadimplanted mice were significantly higher than that in PGA thread group on day 11 after depilation. In particular, the skin tissue of gold thread-implanted mice showed stronger PCNA staining and higher collagen density compared with control mice. These results indicate that gold thread implantation can be an effective way to promote hair re-growth although further confirmatory study is needed for more information on therapeutic mechanisms and long-term safety. PMID:29399026

Local search for optimal global map generation using mid-decadal landsat images

Science.gov (United States)

Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.

2007-01-01

NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

A Novel Particle Swarm Optimization Algorithm for Global Optimization.

Science.gov (United States)

Wang, Chun-Feng; Liu, Kui

2016-01-01

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms.

Carbon Nanotube Thread Electrochemical Cell: Detection of Heavy Metals.

Science.gov (United States)

Zhao, Daoli; Siebold, David; Alvarez, Noe T; Shanov, Vesselin N; Heineman, William R

2017-09-19

In this work, all three electrodes in an electrochemical cell were fabricated based on carbon nanotube (CNT) thread. CNT thread partially insulated with a thin polystyrene coating to define the microelectrode area was used as the working electrode; bare CNT thread was used as the auxiliary electrode; and a micro quasi-reference electrode was fabricated by electroplating CNT thread with Ag and then anodizing it in chloride solution to form a layer of AgCl. The Ag|AgCl coated CNT thread electrode provided a stable potential comparable to the conventional liquid-junction type Ag|AgCl reference electrode. The CNT thread auxiliary electrode provided a stable current, which is comparable to a Pt wire auxiliary electrode. This all-CNT thread three electrode cell has been evaluated as a microsensor for the simultaneous determination of trace levels of heavy metal ions by anodic stripping voltammetry (ASV). Hg 2+ , Cu 2+ , and Pb 2+ were used as a representative system for this study. The calculated detection limits (based on the 3σ method) with a 120 s deposition time are 1.05, 0.53, and 0.57 nM for Hg 2+ , Cu 2+ , and Pb 2+ , respectively. These electrodes significantly reduce the dimensions of the conventional three electrode electrochemical cell to the microscale.

Hybrid intelligent optimization methods for engineering problems

Science.gov (United States)

Pehlivanoglu, Yasin Volkan

quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.

Applications of functional analysis to optimal control problems

International Nuclear Information System (INIS)

Mizukami, K.

1976-01-01

Some basic concepts in functional analysis, a general norm, the Hoelder inequality, functionals and the Hahn-Banach theorem are described; a mathematical formulation of two optimal control problems is introduced by the method of functional analysis. The problem of time-optimal control systems with both norm constraints on control inputs and on state variables at discrete intermediate times is formulated as an L-problem in the theory of moments. The simplex method is used for solving a non-linear minimizing problem inherent in the functional analysis solution to this problem. Numerical results are presented for a train operation. The second problem is that of optimal control of discrete linear systems with quadratic cost functionals. The problem is concerned with the case of unconstrained control and fixed endpoints. This problem is formulated in terms of norms of functionals on suitable Banach spaces. (author)

A Multi-threaded Version of Field II

DEFF Research Database (Denmark)

Jensen, Jørgen Arendt

2014-01-01

A multi-threaded version of Field II has been developed, which automatically can use the multi-core capabil- ities of modern CPUs. The memory allocation routines were rewritten to minimize the number of dynamic allocations and to make pre-allocations possible for each thread. This ensures...... that the simulation job can be automatically partitioned and the interdependence between threads minimized. The new code has been compared to Field II version 3.22, October 27, 2013 (latest free-ware version). A 64 element 5 MHz focused array transducer was simulated. One million point scatterers randomly distributed...... in a plane of 20 x 50 mm (width x depth) with random Gaussian amplitudes were simulated using the command calc scat . Dual Intel Xeon CPU E5-2630 2.60 GHz CPUs were used under Ubuntu Linux 10.02 and Matlab version 2013b. Each CPU holds 6 cores with hyper-threading, corresponding to a total of 24 hyper...

Multi-threaded software framework development for the ATLAS experiment

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00226135; Baines, John; Bold, Tomasz; Calafiura, Paolo; Dotti, Andrea; Farrell, Steven; Leggett, Charles; Malon, David; Ritsch, Elmar; Snyder, Scott; Tsulaia, Vakhtang; van Gemmeren, Peter; Wynne, Benjamin

2016-01-01

ATLAS's current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognised for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. ATLAS examined the requirements on an updated multi-threaded framework and laid out plans for a new framework, including better support for high level trigger (HLT) use cases, in 2014. In this paper we report on our progress in developing the new multi-threaded task parallel extension of Athena, AthenaMT. Implementing AthenaMT has required many significant code changes. Progress has been made in updating key concepts of the framework, to allow the incorporation of different levels of thread safety in algorithmic code (from un-migrated thread-unsafe code, to thread safe copyable code to reentrant co...

Multi-threaded Software Framework Development for the ATLAS Experiment

CERN Document Server

Stewart, Graeme; The ATLAS collaboration; Baines, John; Calafiura, Paolo; Dotti, Andrea; Farrell, Steven; Leggett, Charles; Malon, David; Ritsch, Elmar; Snyder, Scott; Tsulaia, Vakhtang; van Gemmeren, Peter; Wynne, Benjamin

2016-01-01

ATLAS's current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognised for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. ATLAS examined the requirements on an updated multi-threaded framework and layed out plans for a new framework, including better support for high level trigger (HLT) use cases, in 2014. In this paper we report on our progress in developing the new multi-threaded task parallel extension of Athena, AthenaMT. Implementing AthenaMT has required many significant code changes. Progress has been made in updating key concepts of the framework, to allow the incorporation of different levels of thread safety in algorithmic code (from un-migrated thread-unsafe code, to thread safe copyable code to reentrant c...

3D Topology optimization of Stokes flow problems

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan; Dammann, Bernd

of energy efficient devices for 2D Stokes flow. Creeping flow problems are described by the Stokes equations which model very viscous fluids at macro scales or ordinary fluids at very small scales. The latter gives the motivation for topology optimization problems based on the Stokes equations being a model......The present talk is concerned with the application of topology optimization to creeping flow problems in 3D. This research is driven by the fact that topology optimization has proven very successful as a tool in academic and industrial design problems. Success stories are reported from such diverse...

The optimal graph partitioning problem

DEFF Research Database (Denmark)

Sørensen, Michael Malmros; Holm, Søren

1993-01-01

. This problem can be formulated as a MILP, which turns out to be completely symmetrical with respect to the p classes, and the gap between the relaxed LP solution and the optimal solution is the largest one possible. These two properties make it very difficult to solve even smaller problems. In this paper...

Thread selection according to predefined power characteristics during context switching on compute nodes

Science.gov (United States)

None, None

2013-06-04

Methods, apparatus, and products are disclosed for thread selection during context switching on a plurality of compute nodes that includes: executing, by a compute node, an application using a plurality of threads of execution, including executing one or more of the threads of execution; selecting, by the compute node from a plurality of available threads of execution for the application, a next thread of execution in dependence upon power characteristics for each of the available threads; determining, by the compute node, whether criteria for a thread context switch are satisfied; and performing, by the compute node, the thread context switch if the criteria for a thread context switch are satisfied, including executing the next thread of execution.

Stepwise optimization and global chaos of nonlinear parameters in exact calculations of few-particle systems

International Nuclear Information System (INIS)

Frolov, A.M.

1986-01-01

The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He

Nuclear reactor incorporating locking device for threaded bolt connections

International Nuclear Information System (INIS)

Blaushild, R.M.

1987-01-01

A nuclear reactor having a pressure vessel and a first element is described comprising a core barrel situated within the pressure vessel. The core barrel has a baffle former secured in and to the core barrel by bolted connections, and a second element comprising baffle plates secured to the inner surface of the baffle former by bolted connections, with a locking device to prevent loosening of bolted connections between the baffle former and at least one of the elements. The baffle former and at least one element are held together by a headed, threaded bolt engaged in a bore coaxially extending in the baffle former and at least one element and threadedly engaged in a threaded section in at least the baffle former. The threaded section has first threaded of a first direction, with the head of the bolt engaged with a shoulder about the bore in at least one element to hold the baffle formed and at least one element together, the head of the bolt having a first diameter and a cavity, having an unsymmetrical wall thereabout, in the end surface thereof. It comprises a recess in at least one element coaxial with the bore forming a wall thereabout and extending inwardly from the outer surface of at least one element, the recess having a second diameter greater than the first diameter, with at least one element having second threads in the wall of a direction opposite the direction of the first threads of the threaded bore; a locking nut having a base with a downwardly depending cylindrical wall thereabout

Self-cleaning threaded rod spinneret for high-efficiency needleless electrospinning

Science.gov (United States)

Zheng, Gaofeng; Jiang, Jiaxin; Wang, Xiang; Li, Wenwang; Zhong, Weizheng; Guo, Shumin

2018-07-01

High-efficiency production of nanofibers is the key to the application of electrospinning technology. This work focuses on multi-jet electrospinning, in which a threaded rod electrode is utilized as the needless spinneret to achieve high-efficiency production of nanofibers. A slipper block, which fits into and moves through the threaded rod, is designed to transfer polymer solution evenly to the surface of the rod spinneret. The relative motion between the slipper block and the threaded rod electrode promotes the instable fluctuation of the solution surface, thus the rotation of threaded rod electrode decreases the critical voltage for the initial multi-jet ejection and the diameter of nanofibers. The residual solution on the surface of threaded rod is cleaned up by the moving slipper block, showing a great self-cleaning ability, which ensures the stable multi-jet ejection and increases the productivity of nanofibers. Each thread of the threaded rod electrode serves as an independent spinneret, which enhances the electric field strength and constrains the position of the Taylor cone, resulting in high productivity of uniform nanofibers. The diameter of nanofibers decreases with the increase of threaded rod rotation speed, and the productivity increases with the solution flow rate. The rotation of electrode provides an excess force for the ejection of charged jets, which also contributes to the high-efficiency production of nanofibers. The maximum productivity of nanofibers from the threaded rod spinneret is 5-6 g/h, about 250-300 times as high as that from the single-needle spinneret. The self-cleaning threaded rod spinneret is an effective way to realize continuous multi-jet electrospinning, which promotes industrial applications of uniform nanofibrous membrane.

Spatiotemporal radiotherapy planning using a global optimization approach

Science.gov (United States)

Adibi, Ali; Salari, Ehsan

2018-02-01

This paper aims at quantifying the extent of potential therapeutic gain, measured using biologically effective dose (BED), that can be achieved by altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. To that end, a spatiotemporally integrated planning approach is developed, where the spatial and temporal dose modulations are optimized simultaneously. The concept of equivalent uniform BED (EUBED) is used to quantify and compare the clinical quality of spatiotemporally heterogeneous dose distributions in target and critical structures. This gives rise to a large-scale non-convex treatment-plan optimization problem, which is solved using global optimization techniques. The proposed spatiotemporal planning approach is tested on two stylized cancer cases resembling two different tumor sites and sensitivity analysis is performed for radio-biological and EUBED parameters. Numerical results validate that spatiotemporal plans are capable of delivering a larger BED to the target volume without increasing the BED in critical structures compared to conventional time-invariant plans. In particular, this additional gain is attributed to the irradiation of different regions of the target volume at different treatment sessions. Additionally, the trade-off between the potential therapeutic gain and the number of distinct dose distributions is quantified, which suggests a diminishing marginal gain as the number of dose distributions increases.

Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Directory of Open Access Journals (Sweden)

B. Mashadi

Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.

Topology optimization of fluid mechanics problems

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan

While topology optimization for solid continuum structures have been studied for about 20 years and for the special case of trusses for many more years, topology optimization of fluid mechanics problems is more recent. Borrvall and Petersson [1] is the seminal reference for topology optimization......D Navier-Stokes equation as well as an example with convection dominated transport in 2D Stokes flow. Using Stokes flow limits the range of applications; nonetheless, the present work gives a proof-of-concept for the application of the method within fluid mechanics problems and it remains...... processing tool. Prior to design manufacturing this allows the engineer to quantify the performance of the computed topology design using standard, credible analysis tools with a body-fitted mesh. [1] Borrvall and Petersson (2003) "Topology optimization of fluids in Stokes flow", Int. J. Num. Meth. Fluids...

Optimizations of Unstructured Aerodynamics Computations for Many-core Architectures

KAUST Repository

Al Farhan, Mohammed Ahmed

2018-04-13

We investigate several state-of-the-practice shared-memory optimization techniques applied to key routines of an unstructured computational aerodynamics application with irregular memory accesses. We illustrate for the Intel KNL processor, as a representative of the processors in contemporary leading supercomputers, identifying and addressing performance challenges without compromising the floating point numerics of the original code. We employ low and high-level architecture-specific code optimizations involving thread and data-level parallelism. Our approach is based upon a multi-level hierarchical distribution of work and data across both the threads and the SIMD units within every hardware core. On a 64-core KNL chip, we achieve nearly 2.9x speedup of the dominant routines relative to the baseline. These exhibit almost linear strong scalability up to 64 threads, and thereafter some improvement with hyperthreading. At substantially fewer Watts, we achieve up to 1.7x speedup relative to the performance of 72 threads of a 36-core Haswell CPU and roughly equivalent performance to 112 threads of a 56-core Skylake scalable processor. These optimizations are expected to be of value for many other unstructured mesh PDE-based scientific applications as multi and many-core architecture evolves.

Mathematical programming methods for large-scale topology optimization problems

DEFF Research Database (Denmark)

Rojas Labanda, Susana

for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, 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...... 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...

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments.

Science.gov (United States)

Daily, Jeff

2016-02-10

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. A faster intra-sequence local pairwise alignment implementation is described and benchmarked, including new global and semi-global variants. Using a 375 residue query sequence a speed of 136 billion cell updates per second (GCUPS) was achieved on a dual Intel Xeon E5-2670 24-core processor system, the highest reported for an implementation based on Farrar's 'striped' approach. Rognes's SWIPE optimal database search application is still generally the fastest available at 1.2 to at best 2.4 times faster than Parasail for sequences shorter than 500 amino acids. However, Parasail was faster for longer sequences. For global alignments, Parasail's prefix scan implementation is generally the fastest, faster even than Farrar's 'striped' approach, however the opal library is faster for single-threaded applications. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. Applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.

Advances in bio-inspired computing for combinatorial optimization problems

CERN Document Server

Pintea, Camelia-Mihaela

2013-01-01

Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a

Thread angle dependency on flame spread shape over kenaf/polyester combined fabric

Science.gov (United States)

Azahari Razali, Mohd; Sapit, Azwan; Nizam Mohammed, Akmal; Nor Anuar Mohamad, Md; Nordin, Normayati; Sadikin, Azmahani; Faisal Hushim, Mohd; Jaat, Norrizam; Khalid, Amir

2017-09-01

Understanding flame spread behavior is crucial to Fire Safety Engineering. It is noted that the natural fiber exhibits different flame spread behavior than the one of the synthetic fiber. This different may influences the flame spread behavior over combined fabric. There is a research has been done to examined the flame spread behavior over kenaf/polyester fabric. It is seen that the flame spread shape is dependent on the thread angle dependency. However, the explanation of this phenomenon is not described in detail in that research. In this study, explanation about this phenomenon is given in detail. Results show that the flame spread shape is dependent on the position of synthetic thread. For thread angle, θ = 0°, the polyester thread is breaking when the flame approach to the thread and the kenaf thread tends to move to the breaking direction. This behavior produces flame to be ‘V’ shape. However, for thread angle, θ = 90°, the polyester thread melts while the kenaf thread decomposed and burned. At this angle, the distance between kenaf threads remains constant as flame approaches.

Topology optimization for transient heat transfer problems

DEFF Research Database (Denmark)

Zeidan, Said; Sigmund, Ole; Lazarov, Boyan Stefanov

The focus of this work is on passive control of transient heat transfer problems using the topology optimization (TopOpt) method [1]. The goal is to find distributions of a limited amount of phase change material (PCM), within a given design domain, which optimizes the heat energy storage [2]. Our......, TopOpt has later been extended to transient problems in mechanics and photonics (e.g. [5], [6] and [7]). In the presented approach, the optimization is gradient-based, where in each iteration the non-steady heat conduction equation is solved,using the finite element method and an appropriate time......-stepping scheme. A PCM can efficiently absorb heat while keeping its temperature nearly unchanged [8]. The use of PCM ine.g. electronics [9] and mechanics [10], yields improved performance and lower costs depending on a.o., the spatial distribution of PCM.The considered problem consists in optimizing...

Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

Institute of Scientific and Technical Information of China (English)

Zhang Junbin; Cai Jinyan; Meng Yafeng

2016-01-01

Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.

Environmentally acceptable thread compounds: Requirements defined

International Nuclear Information System (INIS)

Stringfellow, W.D.; Hendriks, R.V.; Jacobs, N.L.

1993-01-01

New environmental regulations on thread compounds are now being enforced in several areas with strong maritime tradition and a sensitive environment. These areas include Indonesia, Alaska and portions of Norway. The industry generally recognizes the environmental concerns but, with wider enforcement of regulations imminent, has not been able to define clearly the requirements for environmental compliance. This paper, written in collaboration with The Netherlands State Supervision of Mines, is based on the National Policy on Thread Compounds of The Netherlands. This national policy is representative of policies being followed by other North Sea governments. Similar policies might well be adopted by other governments worldwide. These policies will affect the operator, drilling contractor, and supplier. This paper provides a specific and detailed definition of thread compound requirements by addressing four relevant categories. The categories of interest are regulatory approval, environmental, health, and performance

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

Science.gov (United States)

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

Redoable Tie-Over Dressing Using Multiple Loop Silk Threads

Directory of Open Access Journals (Sweden)

Hyeon Jong Jo

2013-05-01

Full Text Available After skin grafting, to prevent hematoma or seroma collection at the graft site, a tie-over dressing has been commonly used. However, although the conventional tie-over dressing by suture is a useful method for securing a graft site, refixation is difficult when repeated tie-over dressing is needed. Therefore, we recommend a redoable tie-over dressing technique with multiple loops threads and connecting silk threads. After the raw surface of each of our cases was covered with a skin graft, multiple loop silk thread attached with nylon at the skin graft margin. We applied the ointment gauze and wet cotton/fluffy gauze over the skin graft, then fixed the dressing by connecting cross-counter multiple loop thread with connecting silk threads. When we opened the tie-over dressing by cutting the connecting silk threads, we repeated the tie-over dressing with the same method. The skin graft was taken successfully without hematoma or seroma collection or any other complications. In conclusion, we report a novel tie-over dressing enabling simple fixation of the dressing to maintain proper tension for wounds that require repetitive fixation. Further, with this reliable method, the skin grafts were well taken.

Redoable Tie-Over Dressing Using Multiple Loop Silk Threads

Directory of Open Access Journals (Sweden)

Hyeon Jong Jo

2013-05-01

Full Text Available After skin grafting, to prevent hematoma or seroma collection at the graft site, a tie-over dressing has been commonly used. However, although the conventional tie-over dressing by suture is a useful method for securing a graft site, refixation is difficult when repeated tieover dressing is needed. Therefore, we recommend a redoable tie-over dressing technique with multiple loops threads and connecting silk threads. After the raw surface of each of our cases was covered with a skin graft, multiple loop silk thread attached with nylon at the skin graft margin. We applied the ointment gauze and wet cotton/fluffy gauze over the skin graft, then fixed the dressing by connecting cross-counter multiple loop thread with connecting silk threads. When we opened the tie-over dressing by cutting the connecting silk threads, we repeated the tie-over dressing with the same method. The skin graft was taken successfully without hematoma or seroma collection or any other complications. In conclusion, we report a novel tie-over dressing enabling simple fixation of the dressing to maintain proper tension for wounds that require repetitive fixation. Further, with this reliable method, the skin grafts were well taken.

ADVANCED SCHEDULER FOR COOPERATIVE EXECUTION OF THREADS ON MULTI-CORE SYSTEM

Directory of Open Access Journals (Sweden)

O. N. Karasik

2017-01-01

Full Text Available Three architectures of the cooperative thread scheduler in a multithreaded application that is executed on a multi-core system are considered. Architecture A0 is based on the synchronization and scheduling facilities, which are provided by the operating system. Architecture A1 introduces a new synchronization primitive and a single queue of the blocked threads in the scheduler, which reduces the interaction activity between the threads and operating system, and significantly speed up the processes of blocking and unblocking the threads. Architecture A2 replaces the single queue of blocked threads with dedicated queues, one for each of the synchronizing primitives, extends the number of internal states of the primitive, reduces the inter- dependence of the scheduling threads, and further significantly speeds up the processes of blocking and unblocking the threads. All scheduler architectures are implemented on Windows operating systems and based on the User Mode Scheduling. Important experimental results are obtained for multithreaded applications that implement two blocked parallel algorithms of solving the linear algebraic equation systems by the Gaussian elimination. The algorithms differ in the way of the data distribution among threads and by the thread synchronization models. The number of threads varied from 32 to 7936. Architecture A1 shows the acceleration of up to 8.65% and the architecture A2 shows the acceleration of up to 11.98% compared to A0 architecture for the blocked parallel algorithms computing the triangular form and performing the back substitution. On the back substitution stage of the algorithms, architecture A1 gives the acceleration of up to 125%, and architecture A2 gives the acceleration of up to 413% compared to architecture A0. The experiments clearly show that the proposed architectures, A1 and A2 outperform A0 depending on the number of thread blocking and unblocking operations, which happen during the execution of

Using Intel's Knight Landing Processor to Accelerate Global Nested Air Quality Prediction Modeling System (GNAQPMS) Model

Science.gov (United States)

Wang, H.; Chen, H.; Chen, X.; Wu, Q.; Wang, Z.

2016-12-01

The Global Nested Air Quality Prediction Modeling System for Hg (GNAQPMS-Hg) is a global chemical transport model coupled Hg transport module to investigate the mercury pollution. In this study, we present our work of transplanting the GNAQPMS model on Intel Xeon Phi processor, Knights Landing (KNL) to accelerate the model. KNL is the second-generation product adopting Many Integrated Core Architecture (MIC) architecture. Compared with the first generation Knight Corner (KNC), KNL has more new hardware features, that it can be used as unique processor as well as coprocessor with other CPU. According to the Vtune tool, the high overhead modules in GNAQPMS model have been addressed, including CBMZ gas chemistry, advection and convection module, and wet deposition module. These high overhead modules were accelerated by optimizing code and using new techniques of KNL. The following optimized measures was done: 1) Changing the pure MPI parallel mode to hybrid parallel mode with MPI and OpenMP; 2.Vectorizing the code to using the 512-bit wide vector computation unit. 3. Reducing unnecessary memory access and calculation. 4. Reducing Thread Local Storage (TLS) for common variables with each OpenMP thread in CBMZ. 5. Changing the way of global communication from files writing and reading to MPI functions. After optimization, the performance of GNAQPMS is greatly increased both on CPU and KNL platform, the single-node test showed that optimized version has 2.6x speedup on two sockets CPU platform and 3.3x speedup on one socket KNL platform compared with the baseline version code, which means the KNL has 1.29x speedup when compared with 2 sockets CPU platform.

Ringed Seal Search for Global Optimization via a Sensitive Search Model.

Directory of Open Access Journals (Sweden)

Younes Saadi

used in global optimization problems.

Do dual-thread orthodontic mini-implants improve bone/tissue mechanical retention?

Science.gov (United States)

Lin, Yang-Sung; Chang, Yau-Zen; Yu, Jian-Hong; Lin, Chun-Li

2014-12-01

The aim of this study was to understand whether the pitch relationship between micro and macro thread designs with a parametrical relationship in a dual-thread mini-implant can improve primary stability. Three types of mini-implants consisting of single-thread (ST) (0.75 mm pitch in whole length), dual-thread A (DTA) with double-start 0.375 mm pitch, and dual-thread B (DTB) with single-start 0.2 mm pitch in upper 2-mm micro thread region for performing insertion and pull-out testing. Histomorphometric analysis was performed in these specimens in evaluating peri-implant bone defects using a non-contact vision measuring system. The maximum inserted torque (Tmax) in type DTA was found to be the smallest significantly, but corresponding values found no significant difference between ST and DTB. The largest pull-out strength (Fmax) in the DTA mini-implant was found significantly greater than that for the ST mini-implant regardless of implant insertion orientation. Mini-implant engaged the cortical bone well as observed in ST and DTA types. Dual-thread mini-implant with correct micro thread pitch (parametrical relationship with macro thread pitch) in the cortical bone region can improve primary stability and enhanced mechanical retention.

An Improved Harmony Search Based on Teaching-Learning Strategy for Unconstrained Optimization Problems

Directory of Open Access Journals (Sweden)

Shouheng Tuo

2013-01-01

Full Text Available Harmony search (HS algorithm is an emerging population-based metaheuristic algorithm, which is inspired by the music improvisation process. The HS method has been developed rapidly and applied widely during the past decade. In this paper, an improved global harmony search algorithm, named harmony search based on teaching-learning (HSTL, is presented for high dimension complex optimization problems. In HSTL algorithm, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation are employed to maintain the proper balance between convergence and population diversity, and dynamic strategy is adopted to change the parameters. The proposed HSTL algorithm is investigated and compared with three other state-of-the-art HS optimization algorithms. Furthermore, to demonstrate the robustness and convergence, the success rate and convergence analysis is also studied. The experimental results of 31 complex benchmark functions demonstrate that the HSTL method has strong convergence and robustness and has better balance capacity of space exploration and local exploitation on high dimension complex optimization problems.

Comparison of optimal design methods in inverse problems

International Nuclear Information System (INIS)

Banks, H T; Holm, K; Kappel, F

2011-01-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst–Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667–77; De Gaetano A and Arino O 2000 J. Math. Biol. 40 136–68; Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979–90)

Comparison of optimal design methods in inverse problems

Science.gov (United States)

Banks, H. T.; Holm, K.; Kappel, F.

2011-07-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).

Development of Thread-compatible Open Source Stack

Science.gov (United States)

Zimmermann, Lukas; Mars, Nidhal; Schappacher, Manuel; Sikora, Axel

2017-07-01

The Thread protocol is a recent development based on 6LoWPAN (IPv6 over IEEE 802.15.4), but with extensions regarding a more media independent approach, which - additionally - also promises true interoperability. To evaluate and analyse the operation of a Thread network a given open source 6LoWPAN stack for embedded devices (emb::6) has been extended in order to comply with the Thread specification. The implementation covers Mesh Link Establishment (MLE) and network layer functionality as well as 6LoWPAN mesh under routing mechanism based on MAC short addresses. The development has been verified on a virtualization platform and allows dynamical establishment of network topologies based on Thread’s partitioning algorithm.

New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems

Directory of Open Access Journals (Sweden)

Xiguang Li

2017-01-01

Full Text Available Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA, is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two subpopulations, and different subpopulations will undergo different sowing behaviors. Moreover, another sowing method is designed to jump out of local optimum. In order to demonstrate the validation of DA, we compare the proposed algorithm with other existing algorithms, including bat algorithm, particle swarm optimization, and enhanced fireworks algorithm. Simulations show that the proposed algorithm seems much superior to other algorithms. At the same time, the proposed algorithm can be applied to optimize extreme learning machine (ELM for biomedical classification problems, and the effect is considerable. At last, we use different fusion methods to form different fusion classifiers, and the fusion classifiers can achieve higher accuracy and better stability to some extent.

Optimization of the Brillouin operator on the KNL architecture

Science.gov (United States)

Dürr, Stephan

2018-03-01

Experiences with optimizing the matrix-times-vector application of the Brillouin operator on the Intel KNL processor are reported. Without adjustments to the memory layout, performance figures of 360 Gflop/s in single and 270 Gflop/s in double precision are observed. This is with Nc = 3 colors, Nv = 12 right-hand-sides, Nthr = 256 threads, on lattices of size 323 × 64, using exclusively OMP pragmas. Interestingly, the same routine performs quite well on Intel Core i7 architectures, too. Some observations on the much harderWilson fermion matrix-times-vector optimization problem are added.

The Multipoint Global Shape Optimization of Flying Configuration with Movable Leading Edges Flaps

Directory of Open Access Journals (Sweden)

Adriana NASTASE

2012-12-01

Full Text Available The aerodynamical global optimized (GO shape of flying configuration (FC, at two cruising Mach numbers, can be realized by morphing. Movable leading edge flaps are used for this purpose. The equations of the surfaces of the wing, of the fuselage and of the flaps in stretched position are approximated in form of superpositions of homogeneous polynomes in two variables with free coefficients. These coefficients together with the similarity parameters of the planform of the FC are the free parameters of the global optimization. Two enlarged variational problems with free boundaries occur. The first one consists in the determination of the GO shape of the wing-fuselageFC, with the flaps in retracted position, which must be of minimum drag, at higher cruising Mach number. The second enlarged variational problem consists in the determination of the GO shape of the flaps in stretched position in such a manner that the entire FC shall be of minimum drag at the second lower Mach number. The iterative optimum-optimorum (OO theory of the author is used for the solving of these both enlarged variational problems. The inviscid GO shape of the FC is used only in the first step of iteration and the own developed hybrid solutions for the compressible Navier-Stokes partial-differential equations (PDEs are used for the determination of the friction drag coefficient and up the second step of iteration of OO theory.

Application of Multiple-Population Genetic Algorithm in Optimizing the Train-Set Circulation Plan Problem

Directory of Open Access Journals (Sweden)

Yu Zhou

2017-01-01

Full Text Available The train-set circulation plan problem (TCPP belongs to the rolling stock scheduling (RSS problem and is similar to the aircraft routing problem (ARP in airline operations and the vehicle routing problem (VRP in the logistics field. However, TCPP involves additional complexity due to the maintenance constraint of train-sets: train-sets must conduct maintenance tasks after running for a certain time and distance. The TCPP is nondeterministic polynomial hard (NP-hard. There is no available algorithm that can obtain the optimal global solution, and many factors such as the utilization mode and the maintenance mode impact the solution of the TCPP. This paper proposes a train-set circulation optimization model to minimize the total connection time and maintenance costs and describes the design of an efficient multiple-population genetic algorithm (MPGA to solve this model. A realistic high-speed railway (HSR case is selected to verify our model and algorithm, and, then, a comparison of different algorithms is carried out. Furthermore, a new maintenance mode is proposed, and related implementation requirements are discussed.

Optimal management with hybrid dynamics : The shallow lake problem

NARCIS (Netherlands)

Reddy, P.V.; Schumacher, Hans; Engwerda, Jacob; Camlibel, M.K.; Julius, A.A.; Pasumarthy, R.

2015-01-01

In this article we analyze an optimal management problem that arises in ecological economics using hybrid systems modeling. First, we introduce a discounted autonomous infinite horizon hybrid optimal control problem and develop few tools to analyze the necessary conditions for optimality. Next,

A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

Directory of Open Access Journals (Sweden)

Qingyang Zhang

2015-02-01

Full Text Available Bird Mating Optimizer (BMO is a novel meta-heuristic optimization algorithm inspired by intelligent mating behavior of birds. However, it is still insufficient in convergence of speed and quality of solution. To overcome these drawbacks, this paper proposes a hybrid algorithm (TLBMO, which is established by combining the advantages of Teaching-learning-based optimization (TLBO and Bird Mating Optimizer (BMO. The performance of TLBMO is evaluated on 23 benchmark functions, and compared with seven state-of-the-art approaches, namely BMO, TLBO, Artificial Bee Bolony (ABC, Particle Swarm Optimization (PSO, Fast Evolution Programming (FEP, Differential Evolution (DE, Group Search Optimization (GSO. Experimental results indicate that the proposed method performs better than other existing algorithms for global numerical optimization.

Security threads: effective security devices in the past, present, and future

Science.gov (United States)

Wolpert, Gary R.

2002-04-01

Security threads were first used to secure banknotes in the mid 1800's. The key to their anti-counterfeiting success was the fact that by being embedded in the paper, they became an integral part of the banknote substrate. Today, all major currencies still utilize this effective security feature. Technological developments have allowed security threads to evolve from a feature authenticated by only visual means to devices that incorporate both visual and machine detectable components. When viewed from the perspective of a thread being a carrier of various security technologies and the fact that they can be incorporated into the core substrate of banknotes, documents, labels, packaging and some high valued articles, it is clear that security threads will remain as effective security devices well into the future. This paper discusses a brief historical background of security threads, current visual and machine authentication technologies incorporated into threads today and a look to the future of threads as effective security devices.

Topology optimization problems with design-dependent sets of constraints

DEFF Research Database (Denmark)

Schou, Marie-Louise Højlund

Topology optimization is a design tool which is used in numerous fields. It can be used whenever the design is driven by weight and strength considerations. The basic concept of topology optimization is the interpretation of partial differential equation coefficients as effective material...... properties and designing through changing these coefficients. For example, consider a continuous structure. Then the basic concept is to represent this structure by small pieces of material that are coinciding with the elements of a finite element model of the structure. This thesis treats stress constrained...... structural topology optimization problems. For such problems a stress constraint for an element should only be present in the optimization problem when the structural design variable corresponding to this element has a value greater than zero. We model the stress constrained topology optimization problem...

The application of weight windows to 'Global' Monte Carlo problems

International Nuclear Information System (INIS)

Becker, T. L.; Larsen, E. W.

2009-01-01

This paper describes two basic types of global deep-penetration (shielding) problems-the global flux problem and the global response problem. For each of these, two methods for generating weight windows are presented. The first approach, developed by the authors of this paper and referred to generally as the Global Weight Window, constructs a weight window that distributes Monte Carlo particles according to a user-specified distribution. The second approach, developed at Oak Ridge National Laboratory and referred to as FW-CADIS, constructs a weight window based on intuitively extending the concept of the source-detector problem to global problems. The numerical results confirm that the theory used to describe the Monte Carlo particle distribution for a given weight window is valid and that the figure of merit is strongly correlated to the Monte Carlo particle distribution. Furthermore, they illustrate that, while both methods are capable of obtaining the correct solution, the Global Weight Window distributes particles much more uniformly than FW-CADIS. As a result, the figure of merit is higher for the Global Weight Window. (authors)

Globally Optimal Segmentation of Permanent-Magnet Systems

DEFF Research Database (Denmark)

Insinga, Andrea Roberto; Bjørk, Rasmus; Smith, Anders

2016-01-01

Permanent-magnet systems are widely used for generation of magnetic fields with specific properties. The reciprocity theorem, an energy-equivalence principle in magnetostatics, can be employed to calculate the optimal remanent flux density of the permanent-magnet system, given any objective...... remains unsolved. We show that the problem of optimal segmentation of a two-dimensional permanent-magnet assembly with respect to a linear objective functional can be reduced to the problem of piecewise linear approximation of a plane curve by perimeter maximization. Once the problem has been cast...

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

Science.gov (United States)

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Ant Colony Optimization and the Minimum Cut Problem

DEFF Research Database (Denmark)

Kötzing, Timo; Lehre, Per Kristian; Neumann, Frank

2010-01-01

Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization problems. With this paper we contribute to the theoretical understanding of this kind of algorithm by investigating the classical minimum cut problem. An ACO algorithm similar to the one that was prov...

Belief Propagation Algorithm for Portfolio Optimization Problems.

Science.gov (United States)

Shinzato, Takashi; Yasuda, Muneki

2015-01-01

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

Belief Propagation Algorithm for Portfolio Optimization Problems.

Directory of Open Access Journals (Sweden)

Takashi Shinzato

Full Text Available The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

Threaded cognition: an integrated theory of concurrent multitasking.

Science.gov (United States)

Salvucci, Dario D; Taatgen, Niels A

2008-01-01

The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking--that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed across other available resources (e.g., perceptual and motor resources). The theory specifies a parsimonious mechanism that allows for concurrent execution, resource acquisition, and resolution of resource conflicts, without the need for specialized executive processes. By instantiating this mechanism as a computational model, threaded cognition provides explicit predictions of how multitasking behavior can result in interference, or lack thereof, for a given set of tasks. The authors illustrate the theory in model simulations of several representative domains ranging from simple laboratory tasks such as dual-choice tasks to complex real-world domains such as driving and driver distraction. (c) 2008 APA, all rights reserved

Parallel Global Optimization with the Particle Swarm Algorithm (Preprint)

National Research Council Canada - National Science Library

Schutte, J. F; Reinbolt, J. A; Fregly, B. J; Haftka, R. T; George, A. D

2004-01-01

.... To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the Particle Swarm Optimization (PSO) algorithm...

Utilizing Problem Structure in Optimization of Radiation Therapy

International Nuclear Information System (INIS)

Carlsson, Fredrik

2008-04-01

In this thesis, optimization approaches for intensity-modulated radiation therapy are developed and evaluated with focus on numerical efficiency and treatment delivery aspects. The first two papers deal with strategies for solving fluence map optimization problems efficiently while avoiding solutions with jagged fluence profiles. The last two papers concern optimization of step-and-shoot parameters with emphasis on generating treatment plans that can be delivered efficiently and accurately. In the first paper, the problem dimension of a fluence map optimization problem is reduced through a spectral decomposition of the Hessian of the objective function. The weights of the eigenvectors corresponding to the p largest eigenvalues are introduced as optimization variables, and the impact on the solution of varying p is studied. Including only a few eigenvector weights results in faster initial decrease of the objective value, but with an inferior solution, compared to optimization of the bixel weights. An approach combining eigenvector weights and bixel weights produces improved solutions, but at the expense of the pre-computational time for the spectral decomposition. So-called iterative regularization is performed on fluence map optimization problems in the second paper. The idea is to find regular solutions by utilizing an optimization method that is able to find near-optimal solutions with non-jagged fluence profiles in few iterations. The suitability of a quasi-Newton sequential quadratic programming method is demonstrated by comparing the treatment quality of deliverable step-and-shoot plans, generated through leaf sequencing with a fixed number of segments, for different number of bixel-weight iterations. A conclusion is that over-optimization of the fluence map optimization problem prior to leaf sequencing should be avoided. An approach for dynamically generating multileaf collimator segments using a column generation approach combined with optimization of

Global optimization of silicon nanowires for efficient parametric processes

DEFF Research Database (Denmark)

Vukovic, Dragana; Xu, Jing; Mørk, Jesper

2013-01-01

We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions.......We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions....

STATEMENT OF THE OPTIMIZATION PROBLEM OF CARBON PRODUCTS PRODUCTION

Directory of Open Access Journals (Sweden)

O. A. Zhuchenko

2016-08-01

Full Text Available The paper formulated optimization problem formulation production of carbon products. The analysis of technical and economic parameters that can be used to optimize the production of carbonaceous products had been done by the author. To evaluate the efficiency of the energy-intensive production uses several technical and economic indicators. In particular, the specific cost, productivity, income and profitability of production. Based on a detailed analysis had been formulated optimality criterion that takes into account the technological components of profitability. The components in detail the criteria and the proposed method of calculating non-trivial, one of them - the production cost of each product. When solving the optimization problem of technological modes of production into account constraints on the variables are optimized. Thus, restrictions may be expressed on the number of each product produced. Have been formulated the method of calculating the cost per unit of product. Attention is paid to the quality indices of finished products as an additional constraint in the optimization problem. As a result have been formulated the general problem of optimizing the production of carbon products, which includes the optimality criterion and restrictions.

Globally convergent optimization algorithm using conservative convex separable diagonal quadratic approximations

NARCIS (Netherlands)

Groenwold, A.A.; Wood, D.W.; Etman, L.F.P.; Tosserams, S.

2009-01-01

We implement and test a globally convergent sequential approximate optimization algorithm based on (convexified) diagonal quadratic approximations. The algorithm resides in the class of globally convergent optimization methods based on conservative convex separable approximations developed by

Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

Directory of Open Access Journals (Sweden)

Akemi Gálvez

2014-01-01

for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Some Optimization Problems for p-Laplacian Type Equations

International Nuclear Information System (INIS)

Del Pezzo, L. M.; Fernandez Bonder, J.

2009-01-01

In this paper we study some optimization problems for nonlinear elastic membranes. More precisely, we consider the problem of optimizing the cost functional over some admissible class of loads f where u is the (unique) solution to the problem -Δ p u+ vertical bar u vertical bar p-2 u=0 in Ω with vertical bar ∇u vertical bar p-2 u ν =f on ∂Ω

Multiparameter Optimization for Electromagnetic Inversion Problem

Directory of Open Access Journals (Sweden)

M. Elkattan

2017-10-01

Full Text Available Electromagnetic (EM methods have been extensively used in geophysical investigations such as mineral and hydrocarbon exploration as well as in geological mapping and structural studies. In this paper, we developed an inversion methodology for Electromagnetic data to determine physical parameters of a set of horizontal layers. We conducted Forward model using transmission line method. In the inversion part, we solved multi parameter optimization problem where, the parameters are conductivity, dielectric constant, and permeability of each layer. The optimization problem was solved by simulated annealing approach. The inversion methodology was tested using a set of models representing common geological formations.

Interactive Cosegmentation Using Global and Local Energy Optimization

OpenAIRE

Xingping Dong,; Jianbing Shen,; Shao, Ling; Yang, Ming-Hsuan

2015-01-01

We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles to build the Gaussian mixture model and improve the cosegmentation performance. The second one is a global constraint, which attempts to match the histograms of common objects. To minimize the local energy, we apply the spline regression to learn the smoothne...

Solving Multiobjective Optimization Problems Using Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Wenping Zou

2011-01-01

Full Text Available Multiobjective optimization has been a difficult problem and focus for research in fields of science and engineering. This paper presents a novel algorithm based on artificial bee colony (ABC to deal with multi-objective optimization problems. ABC is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. It uses less control parameters, and it can be efficiently used for solving multimodal and multidimensional optimization problems. Our algorithm uses the concept of Pareto dominance to determine the flight direction of a bee, and it maintains nondominated solution vectors which have been found in an external archive. The proposed algorithm is validated using the standard test problems, and simulation results show that the proposed approach is highly competitive and can be considered a viable alternative to solve multi-objective optimization problems.

Global-Local Analysis and Optimization of a Composite Civil Tilt-Rotor Wing

Science.gov (United States)

Rais-Rohani, Masound

1999-01-01

This report gives highlights of an investigation on the design and optimization of a thin composite wing box structure for a civil tilt-rotor aircraft. Two different concepts are considered for the cantilever wing: (a) a thin monolithic skin design, and (b) a thick sandwich skin design. Each concept is examined with three different skin ply patterns based on various combinations of 0, +/-45, and 90 degree plies. The global-local technique is used in the analysis and optimization of the six design models. The global analysis is based on a finite element model of the wing-pylon configuration while the local analysis uses a uniformly supported plate representing a wing panel. Design allowables include those on vibration frequencies, panel buckling, and material strength. The design optimization problem is formulated as one of minimizing the structural weight subject to strength, stiffness, and d,vnamic constraints. Six different loading conditions based on three different flight modes are considered in the design optimization. The results of this investigation reveal that of all the loading conditions the one corresponding to the rolling pull-out in the airplane mode is the most stringent. Also the frequency constraints are found to drive the skin thickness limits, rendering the buckling constraints inactive. The optimum skin ply pattern for the monolithic skin concept is found to be (((0/+/-45/90/(0/90)(sub 2))(sub s))(sub s), while for the sandwich skin concept the optimal ply pattern is found to be ((0/+/-45/90)(sub 2s))(sub s).

Multi-Material Design Optimization of Composite Structures

DEFF Research Database (Denmark)

Hvejsel, Christian Frier

properties. The modeling encompasses discrete orientationing of orthotropic materials, selection between different distinct materials as well as removal of material representing holes in the structure within a unified parametrization. The direct generalization of two-phase topology optimization to any number...... of a relaxation-based search heuristic that accelerates a Generalized Benders' Decomposition technique for global optimization and enables the solution of medium-scale problems to global optimality. Improvements in the ability to solve larger problems to global optimality are found and potentially further...... improvements may be obtained with this technique in combination with cheaper heuristics....

Optimal perturbations for nonlinear systems using graph-based optimal transport

Science.gov (United States)

Grover, Piyush; Elamvazhuthi, Karthik

2018-06-01

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on the phase space to a final measure in finite time. The measure is propagated under system dynamics in between the perturbations via the associated transfer operator. Each perturbation is described by a deterministic map in the measure space that implements a version of Monge-Kantorovich optimal transport with quadratic cost. Hence, the optimal solution minimizes a sum of quadratic costs on phase space transport due to the perturbations applied at specified times. The action of the transport map is approximated by a continuous pseudo-time flow on a graph, resulting in a tractable convex optimization problem. This problem is solved via state-of-the-art solvers to global optimality. We apply this algorithm to a problem of transport between measures supported on two disjoint almost-invariant sets in a chaotic fluid system, and to a finite-time optimal mixing problem by choosing the final measure to be uniform. In both cases, the optimal perturbations are found to exploit the phase space structures, such as lobe dynamics, leading to efficient global transport. As the time-horizon of the problem is increased, the optimal perturbations become increasingly localized. Hence, by combining the transfer operator approach with ideas from the theory of optimal mass transportation, we obtain a discrete-time graph-based algorithm for optimal transport and mixing in nonlinear systems.

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

Science.gov (United States)

Rash, James

2014-01-01

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization

ON PROBLEM OF REGIONAL WAREHOUSE AND TRANSPORT INFRASTRUCTURE OPTIMIZATION

Directory of Open Access Journals (Sweden)

I. Yu. Miretskiy

2017-01-01

Full Text Available The article suggests an approach of solving the problem of warehouse and transport infrastructure optimization in a region. The task is to determine the optimal capacity and location of the support network of warehouses in the region, as well as power, composition and location of motor fleets. Optimization is carried out using mathematical models of a regional warehouse network and a network of motor fleets. These models are presented as mathematical programming problems with separable functions. The process of finding the optimal solution of problems is complicated due to high dimensionality, non-linearity of functions, and the fact that a part of variables are constrained to integer, and some variables can take values only from a discrete set. Given the mentioned above complications search for an exact solution was rejected. The article suggests an approximate approach to solving problems. This approach employs effective computational schemes for solving multidimensional optimization problems. We use the continuous relaxation of the original problem to obtain its approximate solution. An approximately optimal solution of continuous relaxation is taken as an approximate solution of the original problem. The suggested solution method implies linearization of the obtained continuous relaxation and use of the separable programming scheme and the scheme of branches and bounds. We describe the use of the simplex method for solving the linearized continuous relaxation of the original problem and the specific moments of the branches and bounds method implementation. The paper shows the finiteness of the algorithm and recommends how to accelerate process of finding a solution.

Performance improvement of developed program by using multi-thread technique

Directory of Open Access Journals (Sweden)

Surasak Jabal

2015-03-01

Full Text Available This research presented how to use a multi-thread programming technique to improve the performance of a program written by Windows Presentation Foundation (WPF. The Computer Assisted Instruction (CAI software, named GAME24, was selected to use as a case study. This study composed of two main parts. The first part was about design and modification of the program structure upon the Object Oriented Programing (OOP approach. The second part was about coding the program using the multi-thread technique which the number of threads were based on the calculated Catalan number. The result showed that the multi-thread programming technique increased the performance of the program 44%-88% compared to the single-thread technique. In addition, it has been found that the number of cores in the CPU also increase the performance of multithreaded program proportionally.

Kernel optimization for short-range molecular dynamics

Science.gov (United States)

Hu, Changjun; Wang, Xianmeng; Li, Jianjiang; He, Xinfu; Li, Shigang; Feng, Yangde; Yang, Shaofeng; Bai, He

2017-02-01

To optimize short-range force computations in Molecular Dynamics (MD) simulations, multi-threading and SIMD optimizations are presented in this paper. With respect to multi-threading optimization, a Partition-and-Separate-Calculation (PSC) method is designed to avoid write conflicts caused by using Newton's third law. Serial bottlenecks are eliminated with no additional memory usage. The method is implemented by using the OpenMP model. Furthermore, the PSC method is employed on Intel Xeon Phi coprocessors in both native and offload models. We also evaluate the performance of the PSC method under different thread affinities on the MIC architecture. In the SIMD execution, we explain the performance influence in the PSC method, considering the "if-clause" of the cutoff radius check. The experiment results show that our PSC method is relatively more efficient compared to some traditional methods. In double precision, our 256-bit SIMD implementation is about 3 times faster than the scalar version.

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

International Nuclear Information System (INIS)

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

2006-01-01

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

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

Energy Technology Data Exchange (ETDEWEB)

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

2006-09-15

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

Creating and improving multi-threaded Geant4

CERN Document Server

Dong, Xin; Apostolakis, John; Jarp, Sverre; Nowak, Andrzej; Asai, Makoto; Brandt, Daniel

2012-01-01

We document the methods used to create the multi-threaded prototype Geant4MT from a sequential version of Geant4. We cover the Source-to-Source transformations applied, and discuss the process of verifying the correctness of the Geant4MT toolkit and applications based on it. Tools to ensure that the results of a transformed multi-threaded application are exactly equal to the original sequential version are under development. Stand-alone or simple applications can be adapted within 1-2 working days. Geant4MT is shown to scale linearly on an 80-core computer. In the special case of a single worker thread on one core, 30% overhead has been observed. We explain the reasons for this and the improvements introduced to reduce this overhead.

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Shifeng Chen

2017-09-01

Full Text Available The dynamic vehicle routing problem (DVRP is a variant of the Vehicle Routing Problem (VRP in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance. In this paper, we propose a monarch butterfly optimization (MBO algorithm to solve DVRPs, utilizing a greedy strategy. Both migration operation and the butterfly adjusting operator only accept the offspring of butterfly individuals that have better fitness than their parents. To improve performance, a later perturbation procedure is implemented, to maintain a balance between global diversification and local intensification. The computational results indicate that the proposed technique outperforms the existing approaches in the literature for average performance by at least 9.38%. In addition, 12 new best solutions were found. This shows that this proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the DVRP.

Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem

Directory of Open Access Journals (Sweden)

Ho-Yoeng Yun

2013-01-01

Full Text Available We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO to effectively solve the Traveling Salesman Problem (TSP. The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed to validate the efficiency of our algorithm through a comparison with other algorithms and the optimum solutions presented in the TSPLIB. The results indicate that our algorithm is capable of generating the optimum solution for most instances in the TSPLIB; moreover, our algorithm found better solutions in two cases (kroB100 and pr144 when compared with the optimum solution presented in the TSPLIB.

Random Matrix Approach for Primal-Dual Portfolio Optimization Problems

Science.gov (United States)

Tada, Daichi; Yamamoto, Hisashi; Shinzato, Takashi

2017-12-01

In this paper, we revisit the portfolio optimization problems of the minimization/maximization of investment risk under constraints of budget and investment concentration (primal problem) and the maximization/minimization of investment concentration under constraints of budget and investment risk (dual problem) for the case that the variances of the return rates of the assets are identical. We analyze both optimization problems by the Lagrange multiplier method and the random matrix approach. Thereafter, we compare the results obtained from our proposed approach with the results obtained in previous work. Moreover, we use numerical experiments to validate the results obtained from the replica approach and the random matrix approach as methods for analyzing both the primal and dual portfolio optimization problems.

On a Highly Nonlinear Self-Obstacle Optimal Control Problem

Energy Technology Data Exchange (ETDEWEB)

Di Donato, Daniela, E-mail: daniela.didonato@unitn.it [University of Trento, Department of Mathematics (Italy); Mugnai, Dimitri, E-mail: dimitri.mugnai@unipg.it [Università di Perugia, Dipartimento di Matematica e Informatica (Italy)

2015-10-15

We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.

On global environment problems in electric power business

International Nuclear Information System (INIS)

Sugi, Masashi

1992-01-01

The former environmental problems were atmospheric pollution, water quality contamination, noise and vibration nuisance, waste disposal and so on mainly at interior or district level, but now, the influence that the problems such as the global warming due to carbon dioxide emission, the ozone layer breaking due to freon gas, acid rain going over boundaries and so on exert to environment spreads to wide areas, therefore, various research and investigation have been carried out as the environmental problems on global scale at national and international levels. It has become an important subject to make the preservation of global environment and durable economical development compatible by effectively utilizing limited resources and energy. The electric power companies have advanced positively the prevention of pollution and the preservation of environment, and attained the environment preservation of top level in the world. The consciousness of people on environmental problems has heightened, therefore the construction and operation of power plants harmonized to districts are important. The countermeasures to environmental problems taken by electric power companies are reported. (K.I.)

The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems

Directory of Open Access Journals (Sweden)

Henryk Josiński

2014-01-01

Full Text Available This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO distinguished by the hybrid strategy of the search space exploration proposed by the authors. The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem. The achieved results are compared with analogous outcomes produced by other optimization methods reported in the literature.

Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method

Energy Technology Data Exchange (ETDEWEB)

Jun Sun; Wei Fang; Daojun Wang; Wenbo Xu [School of Information Technology, Jiangnan Univ., Wuxi, Jiangsu 214122 (China)

2009-12-15

In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO-DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO-DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm. (author)

Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method

International Nuclear Information System (INIS)

Sun Jun; Fang Wei; Wang Daojun; Xu Wenbo

2009-01-01

In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO-DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO-DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm.

UTLEON3 Exploring Fine-Grain Multi-Threading in FPGAs

CERN Document Server

Daněk, Martin; Kohout, Lukáš; Sýkora, Jaroslav; Bartosinski, Roman

2013-01-01

This book describes a specification, microarchitecture, VHDL implementation and evaluation of a SPARC v8 CPU with fine-grain multi-threading, called micro-threading. The CPU, named UTLEON3, is an alternative platform for exploring CPU multi-threading that is compatible with the industry-standard GRLIB package. The processor microarchitecture was designed to map in an efficient way the data-flow scheme on a classical von Neumann pipelined processing used in common processors, while retaining full binary compatibility with existing legacy programs.  Describes and documents a working SPARC v8, with fine-grain multithreading and fast context switch; Provides VHDL sources for the described processor; Describes a latency-tolerant framework for coupling hardware accelerators to microthreaded processor pipelines; Includes programming by example in the micro-threaded assembly language.    

Optimization Problems in Supply Chain Management

NARCIS (Netherlands)

D. Romero Morales (Dolores)

2000-01-01

textabstractMaria Dolores Romero Morales was born on Augustus 5th, 1971, in Sevilla (Spain). She studied Mathematics at University of Sevilla from 1989 to 1994 and specialized in Statistics and Operations Research. She wrote her Master's thesis on Global Optimization in Location Theory under the

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.

A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem

Directory of Open Access Journals (Sweden)

Hao Yin

2014-01-01

Full Text Available For SLA-aware service composition problem (SSC, an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively.

Metal and transuranic records in mussel shells, byssal threads and tissues

Science.gov (United States)

Koide, Minoru; Lee, Dong Soo; Goldberg, Edward D.

1982-12-01

Bivalve shells offer several advantages over tissues for the monitoring of heavy metal pollutants in the marine environment. They are easier to handle and to store. The problem of whether to depurate the animals before analyses is avoided. The shells appear to be more sensitive to environmental heavy metals levels over the long term than do the soft parts. Of the substances examined (Cd, Cu, Zn, Pb, Ag, Ni, 238Pu and 239 + 240Pu) only Pb and Pu displayed a strong covariance between soft tissue and shell concentrations. There were strong correlations between metals in the shell but not in the soft tissues in general. The byssal threads, because of their enrichment of transuranic elements and of their ease in handling, may be useful in monitoring these metals. A very weak discharge of 238Pu to marine waters adjacent to a nuclear reactor was detected in the byssal threads of mussels.

Science and technology related global problems: An international survey of science educators

Science.gov (United States)

Bybee, Rodger W.; Mau, Teri

This survey evaluated one aspect of the Science-Technology-Society theme, namely, the teaching of global problems related to science and technology. The survey was conducted during spring 1984. Two hundred sixty-two science educators representing 41 countries completed the survey. Response was 80%. Findings included a ranking of twelve global problems (the top six were: World Hunger and Food Resources, Population Growth, Air Quality and Atmosphere, Water Resources, War Technology, and Human Health and Disease). Science educators generally indicated the following: the science and technology related global problems would be worse by the year 2000; they were slightly or moderately knowledgeable about the problems; print, audio-visual media, and personal experiences were their primary sources of information; it is important to study global problems in schools; emphasis on global problems should increase with age/grade level; an integrated approach should be used to teach about global problems; courses including global problems should be required of all students; most countries are in the early stages of developing programs including global problems; there is a clear trend toward S-T-S; there is public support for including global problems; and, the most significant limitations to implementation of the S-T-S theme (in order of significance) are political, personnel, social, psychological, economic, pedagogical, and physical. Implications for research and development in science education are discussed.

About an Optimal Visiting Problem

Energy Technology Data Exchange (ETDEWEB)

Bagagiolo, Fabio, E-mail: bagagiol@science.unitn.it; Benetton, Michela [Unversita di Trento, Dipartimento di Matematica (Italy)

2012-02-15

In this paper we are concerned with the optimal control problem consisting in minimizing the time for reaching (visiting) a fixed number of target sets, in particular more than one target. Such a problem is of course reminiscent of the famous 'Traveling Salesman Problem' and brings all its computational difficulties. Our aim is to apply the dynamic programming technique in order to characterize the value function of the problem as the unique viscosity solution of a suitable Hamilton-Jacobi equation. We introduce some 'external' variables, one per target, which keep in memory whether the corresponding target is already visited or not, and we transform the visiting problem in a suitable Mayer problem. This fact allows us to overcome the lacking of the Dynamic Programming Principle for the originary problem. The external variables evolve with a hysteresis law and the Hamilton-Jacobi equation turns out to be discontinuous.

Topology Optimization for Transient Wave Propagation Problems

DEFF Research Database (Denmark)

Matzen, René

The study of elastic and optical waves together with intensive material research has revolutionized everyday as well as cutting edge technology in very tangible ways within the last century. Therefore it is important to continue the investigative work towards improving existing as well as innovate...... new technology, by designing new materials and their layout. The thesis presents a general framework for applying topology optimization in the design of material layouts for transient wave propagation problems. In contrast to the high level of modeling in the frequency domain, time domain topology...... optimization is still in its infancy. A generic optimization problem is formulated with an objective function that can be field, velocity, and acceleration dependent, as well as it can accommodate the dependency of filtered signals essential in signal shape optimization [P3]. The analytical design gradients...

Distributed Robust Optimization in Networked System.

Science.gov (United States)

Wang, Shengnan; Li, Chunguang

2016-10-11

In this paper, we consider a distributed robust optimization (DRO) problem, where multiple agents in a networked system cooperatively minimize a global convex objective function with respect to a global variable under the global constraints. The objective function can be represented by a sum of local objective functions. The global constraints contain some uncertain parameters which are partially known, and can be characterized by some inequality constraints. After problem transformation, we adopt the Lagrangian primal-dual method to solve this problem. We prove that the primal and dual optimal solutions of the problem are restricted in some specific sets, and we give a method to construct these sets. Then, we propose a DRO algorithm to find the primal-dual optimal solutions of the Lagrangian function, which consists of a subgradient step, a projection step, and a diffusion step, and in the projection step of the algorithm, the optimized variables are projected onto the specific sets to guarantee the boundedness of the subgradients. Convergence analysis and numerical simulations verifying the performance of the proposed algorithm are then provided. Further, for nonconvex DRO problem, the corresponding approach and algorithm framework are also provided.

Problems of the power plant shield optimization

International Nuclear Information System (INIS)

Abagyan, A.A.; Dubinin, A.A.; Zhuravlev, V.I.; Kurachenko, Yu.A.; Petrov, Eh.E.

1981-01-01

General approaches to the solution of problems on the nuclear power plant radiation shield optimization are considered. The requirements to the shield parameters are formulated in a form of restrictions on a number of functionals, determined by the solution of γ quantum and neutron transport equations or dimensional and weight characteristics of shield components. Functional determined by weight-dimensional parameters (shield cost, mass and thickness) and functionals, determined by radiation fields (equivalent dose rate, produced by neutrons and γ quanta, activation functional, radiation functional, heat flux, integral heat flux in a particular part of the shield volume, total energy flux through a particular shield surface are considered. The following methods of numerical solution of simplified optimization problems are discussed: semiempirical methods using radiation transport physical leaks, numerical solution of approximate transport equations, numerical solution of transport equations for the simplest configurations making possible to decrease essentially a number of variables in the problem. The conclusion is drawn that the attained level of investigations on the problem of nuclear power plant shield optimization gives the possibility to pass on at present to the solution of problems with a more detailed account of the real shield operating conditions (shield temperature field account, its strength and other characteristics) [ru

Solving the Examination Timetabling Problem in GPUs

Directory of Open Access Journals (Sweden)

Vasileios Kolonias

2014-07-01

Full Text Available The examination timetabling problem belongs to the class of combinatorial optimization problems and is of great importance for every University. In this paper, a hybrid evolutionary algorithm running on a GPU is employed to solve the examination timetabling problem. The hybrid evolutionary algorithm proposed has a genetic algorithm component and a greedy steepest descent component. The GPU computational capabilities allow the use of very large population sizes, leading to a more thorough exploration of the problem solution space. The GPU implementation, depending on the size of the problem, is up to twenty six times faster than the identical single-threaded CPU implementation of the algorithm. The algorithm is evaluated with the well known Toronto datasets and compares well with the best results found in the bibliography. Moreover, the selection of the encoding of the chromosomes and the tournament selection size as the population grows are examined and optimized. The compressed sparse row format is used for the conflict matrix and was proven essential to the process, since most of the datasets have a small conflict density, which translates into an extremely sparse matrix.

Structural Analysis of Taper-Threaded Rebar Couplers

International Nuclear Information System (INIS)

Chu, Seok Jae; Kwon, Hyuk Mo; Seo, Sang Hwan

2014-01-01

A number of rebar couplers were developed by the leading companies. The information about the products is available from the company website. However, the theory on the taper-threaded coupler is not available. In this paper, the mechanics of the taper-thread was developed to understand the effect of the tightening torque. Structural analysis of our own newly developed rebar coupler was done to improve the strength of the coupler. The taper-threaded rebar coupler was analyzed. The tightening of the rebar into the coupler developed a circumferential stress in the coupler. The circumferential stress depends on the coefficient of friction as well as the tightening torque. The circumferential stress is less than the allowable stress 20 kgf/mm 2 of the material for the coefficient of friction greater than 0.1. The tightening of the rebar into the coupler and the subsequent tensioning was simulated using CATIA. Linear elastic analysis considering contact was done. The tightening of the taper-threaded rebar developed a uniform stress distribution in both standard coupler and position coupler. On the other hand, the tightening of the nut in the axial direction developed a non-uniform stress distribution. Similarly the tensioning also developed a non-uniform stress distribution

An optimal control approach to manpower planning problem

Directory of Open Access Journals (Sweden)

H. W. J. Lee

2001-01-01

Full Text Available A manpower planning problem is studied in this paper. The model includes scheduling different types of workers over different tasks, employing and terminating different types of workers, and assigning different types of workers to various trainning programmes. The aim is to find an optimal way to do all these while keeping the time-varying demand for minimum number of workers working on each different tasks satisfied. The problem is posed as an optimal discrete-valued control problem in discrete time. A novel numerical scheme is proposed to solve the problem, and an illustrative example is provided.

Topology Optimization of Large Scale Stokes Flow Problems

DEFF Research Database (Denmark)

Aage, Niels; Poulsen, Thomas Harpsøe; Gersborg-Hansen, Allan

2008-01-01

This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.......This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs....

Partnerships as panacea for addressing global problems?

NARCIS (Netherlands)

A. Kolk (Ans)

2013-01-01

textabstractThis chapter examines partnerships and their peculiarities, based on recent research from various disciplines, in the context of the large problems faced by (global) society. These problems are very complex, often cross national boundaries, and cannot easily be 'solved' by one single

High efficiency carbon nanotube thread antennas

Science.gov (United States)

Amram Bengio, E.; Senic, Damir; Taylor, Lauren W.; Tsentalovich, Dmitri E.; Chen, Peiyu; Holloway, Christopher L.; Babakhani, Aydin; Long, Christian J.; Novotny, David R.; Booth, James C.; Orloff, Nathan D.; Pasquali, Matteo

2017-10-01

Although previous research has explored the underlying theory of high-frequency behavior of carbon nanotubes (CNTs) and CNT bundles for antennas, there is a gap in the literature for direct experimental measurements of radiation efficiency. These measurements are crucial for any practical application of CNT materials in wireless communication. In this letter, we report a measurement technique to accurately characterize the radiation efficiency of λ/4 monopole antennas made from the CNT thread. We measure the highest absolute values of radiation efficiency for CNT antennas of any type, matching that of copper wire. To capture the weight savings, we propose a specific radiation efficiency metric and show that these CNT antennas exceed copper's performance by over an order of magnitude at 1 GHz and 2.4 GHz. We also report direct experimental observation that, contrary to metals, the radiation efficiency of the CNT thread improves significantly at higher frequencies. These results pave the way for practical applications of CNT thread antennas, particularly in the aerospace and wearable electronics industries where weight saving is a priority.

Stochastic Linear Quadratic Optimal Control Problems

International Nuclear Information System (INIS)

Chen, S.; Yong, J.

2001-01-01

This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

Energy Technology Data Exchange (ETDEWEB)

Li, Dengwang; Wang, Jie [College of Physics and Electronics, Shandong Normal University, Jinan, Shandong (China); Kapp, Daniel S.; Xing, Lei [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)

2015-06-15

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

International Nuclear Information System (INIS)

Li, Dengwang; Wang, Jie; Kapp, Daniel S.; Xing, Lei

2015-01-01

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization

Directory of Open Access Journals (Sweden)

Feng Zou

2016-01-01

Full Text Available An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO, which is considering the teacher’s behavior influence on the students and the mean grade of the class, is proposed in the paper to find the global solutions of function optimization problems. In this method, the teacher phase of TLBO is modified; the new position of the individual is determined by the old position, the mean position, and the best position of current generation. The method overcomes disadvantage that the evolution of the original TLBO might stop when the mean position of students equals the position of the teacher. To decrease the computation cost of the algorithm, the process of removing the duplicate individual in original TLBO is not adopted in the improved algorithm. Moreover, the probability of local convergence of the improved method is decreased by the mutation operator. The effectiveness of the proposed method is tested on some benchmark functions, and the results are competitive with respect to some other methods.

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

Science.gov (United States)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this

SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

Directory of Open Access Journals (Sweden)

V. Panteleev Andrei

2017-01-01

Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.

Optimization of Multiple Traveling Salesman Problem Based on Simulated Annealing Genetic Algorithm

Directory of Open Access Journals (Sweden)

Xu Mingji

2017-01-01

Full Text Available It is very effective to solve the multi variable optimization problem by using hierarchical genetic algorithm. This thesis analyzes both advantages and disadvantages of hierarchical genetic algorithm and puts forward an improved simulated annealing genetic algorithm. The new algorithm is applied to solve the multiple traveling salesman problem, which can improve the performance of the solution. First, it improves the design of chromosomes hierarchical structure in terms of redundant hierarchical algorithm, and it suggests a suffix design of chromosomes; Second, concerning to some premature problems of genetic algorithm, it proposes a self-identify crossover operator and mutation; Third, when it comes to the problem of weak ability of local search of genetic algorithm, it stretches the fitness by mixing genetic algorithm with simulated annealing algorithm. Forth, it emulates the problems of N traveling salesmen and M cities so as to verify its feasibility. The simulation and calculation shows that this improved algorithm can be quickly converged to a best global solution, which means the algorithm is encouraging in practical uses.

Iron deficiency - a global problem

International Nuclear Information System (INIS)

Ali, S.M.

1993-01-01

Iron deficiency is an important nutritional global problem. This paper contains summery of information gathered from a dietary survey as iron deficiency anaemia is major public health problem in many developing countries including Pakistan. Comparison of anaemia in different age group and sex versus various regions in the world are given. In Pakistan also anaemia is widespread. According to the report of Micro-Nutrient survey of Pakistan 40% of the population are found to have low level of haemoglobin, more than half of pregnant women suffered from marginal or deficient haemoglobin. (A.B.)

Iron deficiency - a global problem

Energy Technology Data Exchange (ETDEWEB)

Ali, S M [Pakistan Council for Science and Technology, Islamabad (Pakistan)

1994-12-31

Iron deficiency is an important nutritional global problem. This paper contains summery of information gathered from a dietary survey as iron deficiency anaemia is major public health problem in many developing countries including Pakistan. Comparison of anaemia in different age group and sex versus various regions in the world are given. In Pakistan also anaemia is widespread. According to the report of Micro-Nutrient survey of Pakistan 40% of the population are found to have low level of haemoglobin, more than half of pregnant women suffered from marginal or deficient haemoglobin. (A.B.).

An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems

Directory of Open Access Journals (Sweden)

Guo-Qiang Zeng

2014-01-01

Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.

Methods for optimizing over the efficient and weakly efficient sets of an affine fractional vector optimization program

DEFF Research Database (Denmark)

Le, T.H.A.; Pham, D. T.; Canh, Nam Nguyen

2010-01-01

Both the efficient and weakly efficient sets of an affine fractional vector optimization problem, in general, are neither convex nor given explicitly. Optimization problems over one of these sets are thus nonconvex. We propose two methods for optimizing a real-valued function over the efficient...... and weakly efficient sets of an affine fractional vector optimization problem. The first method is a local one. By using a regularization function, we reformulate the problem into a standard smooth mathematical programming problem that allows applying available methods for smooth programming. In case...... the objective function is linear, we have investigated a global algorithm based upon a branch-and-bound procedure. The algorithm uses Lagrangian bound coupling with a simplicial bisection in the criteria space. Preliminary computational results show that the global algorithm is promising....

A note on the depth function of combinatorial optimization problems

NARCIS (Netherlands)

Woeginger, G.J.

2001-01-01

In a recent paper [Discrete Appl. Math. 43 (1993) 115–129], Kern formulates two conjectures on the relationship between the computational complexity of computing the depth function of a discrete optimization problem and the computational complexity of solving this optimization problem to optimality.

Essays on variational approximation techniques for stochastic optimization problems

Science.gov (United States)

Deride Silva, Julio A.

This dissertation presents five essays on approximation and modeling techniques, based on variational analysis, applied to stochastic optimization problems. It is divided into two parts, where the first is devoted to equilibrium problems and maxinf optimization, and the second corresponds to two essays in statistics and uncertainty modeling. Stochastic optimization lies at the core of this research as we were interested in relevant equilibrium applications that contain an uncertain component, and the design of a solution strategy. In addition, every stochastic optimization problem relies heavily on the underlying probability distribution that models the uncertainty. We studied these distributions, in particular, their design process and theoretical properties such as their convergence. Finally, the last aspect of stochastic optimization that we covered is the scenario creation problem, in which we described a procedure based on a probabilistic model to create scenarios for the applied problem of power estimation of renewable energies. In the first part, Equilibrium problems and maxinf optimization, we considered three Walrasian equilibrium problems: from economics, we studied a stochastic general equilibrium problem in a pure exchange economy, described in Chapter 3, and a stochastic general equilibrium with financial contracts, in Chapter 4; finally from engineering, we studied an infrastructure planning problem in Chapter 5. We stated these problems as belonging to the maxinf optimization class and, in each instance, we provided an approximation scheme based on the notion of lopsided convergence and non-concave duality. This strategy is the foundation of the augmented Walrasian algorithm, whose convergence is guaranteed by lopsided convergence, that was implemented computationally, obtaining numerical results for relevant examples. The second part, Essays about statistics and uncertainty modeling, contains two essays covering a convergence problem for a sequence

Permission-based separation logic for multi-threaded Java programs

NARCIS (Netherlands)

Amighi, A.; Haack, Christian; Huisman, Marieke; Hurlin, C.

This paper presents a program logic for reasoning about multithreaded Java-like programs with concurrency primitives such as dynamic thread creation, thread joining and reentrant object monitors. The logic is based on concurrent separation logic. It is the first detailed adaptation of concurrent

Investigating Student Use of Technology for Engaged Citizenship in A Global Age

Directory of Open Access Journals (Sweden)

Brad M. Maguth

2012-05-01

Full Text Available This study undertook a five month qualitative investigation into technology use amongst twelve high school social studies students in two different sites in the Midwestern United States. This study examined students’ use of technology and its relationship to three dimensions of citizenship in a global age: understand global events, issues, and perspectives, participate in global networks to communicate and collaborate with global audiences, and advocate on global problems and issues to think and act globally. Collecting data through semi-structured student interviews, online-threaded discussions and document analysis, I triangulated findings, and employed a qualitative approach. The study finds a relationship between student participants’ use of technology and their serving as engaged citizenship in a global age. In using technology, students accessed international news and information, joined global networks to communicate and collaborate with global audiences, and produced digital content for international audiences.

Collaborative learning using VoiceThread in an online graduate course

Directory of Open Access Journals (Sweden)

Yu-Hui Ching

2013-09-01

Full Text Available Collaborative learning enables participants in a learning community to externalize and share knowledge, experiences, and practice. However, collaborative learning in an online environment can be challenging due to the lack of face-to face interaction. This current study examined twenty graduate students’ experiences of using VoiceThread for a collaborative activity in an entirely online course to explore students’ perceptions of using multi-modal communication for collaboration and knowledge sharing. The results of this study revealed that graduate students had very positive experiences toward using VoiceThread for collaborative learning. The participants found VoiceThread easy to learn and use, and reported that audio and video interaction on VoiceThread helped connect them with their peers. More than half of the participants interacted with peers using audio, followed by text and then by video. Half of the students felt they were more connected to peers; however, feeling more connected did not result in more participation as most of the students only participated at the level that met the course requirement. Participants identified benefits and drawbacks of using VoiceThread for collaboration as compared to using text-based discussion forums. The most frequently mentioned benefit of using VoiceThread for collaboration exemplifies its multi-modal affordance that enables learners to communicate emotion, personality, and other non-verbal cues conducive to better understanding and interpretation of meanings. About half of the participants indicated that they preferred VoiceThread to text-based discussion forums for collaborative learning activity. Challenges and implications for future research are also discussed.

Missing IUD Despite Threads at the Cervix

Directory of Open Access Journals (Sweden)

Andrew L. Atkinson

2014-01-01

Full Text Available Today, the intrauterine device (IUD is by far the most popular form of long term reversible contraception in the world. Side effects from the IUD are minimal and complications are rare. Uterine perforation and migration of the IUD outside the uterine cavity are the most serious complications. Physician visualization and/or the patient feeling retrieval threads at the cervical os are confirmation that the IUD has not been expelled or migrated. We present a case of a perforated, intraperitoneal IUD with threads noted at the cervical os. Office removal was not possible using gentle traction on the threads. Multiple imaging and endoscopic modalities were used to try and locate the IUD including pelvic ultrasound, diagnostic hysteroscopy, cystoscopy, and pelvic magnetic resonance imaging (MRI. The studies gave conflicting results on location of the IUD. Ultimately, the missing IUD was removed via laparoscopy.

Replica analysis for the duality of the portfolio optimization problem.

Science.gov (United States)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Replica analysis for the duality of the portfolio optimization problem

Science.gov (United States)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Dependence of the length of solar filament threads on the magnetic configuration

International Nuclear Information System (INIS)

Zhou Yu-Hao; Chen Peng-Fei; Fang Cheng; Zhang Qing-Min

2014-01-01

High-resolution Hα observations indicate that filaments consist of an assembly of thin threads. In quiescent filaments, the threads are generally short, whereas in active region filaments, the threads are generally long. In order to explain these observational features, we performed one-dimensional radiative hydrodynamic simulations of filament formation along a dipped magnetic flux tube in the framework of the chromospheric evaporation-coronal condensation model. The geometry of a dipped magnetic flux tube is characterized by three parameters, i.e., the depth (D), the half-width (w) and the altitude (h) of the magnetic dip. A survey of the parameters in numerical simulations shows that when allowing the filament thread to grow in 5 days, the maximum length (L th ) of the filament thread increases linearly with w, and decreases linearly with D and h. The dependence is fitted into a linear function L th = 0.84w − 0.88D − 2.78h+17.31(Mm). Such a relation can qualitatively explain why quiescent filaments have shorter threads and active region filaments have longer threads

A comparison of global optimization algorithms with standard benchmark functions and real-world applications using Energy Plus

Energy Technology Data Exchange (ETDEWEB)

Kamph, Jerome Henri; Robinson, Darren; Wetter, Michael

2009-09-01

There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimise the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.

Parallel optimization algorithm for drone inspection in the building industry

Science.gov (United States)

Walczyński, Maciej; BoŻejko, Wojciech; Skorupka, Dariusz

2017-07-01

In this paper we present an approach for Vehicle Routing Problem with Drones (VRPD) in case of building inspection from the air. In autonomic inspection process there is a need to determine of the optimal route for inspection drone. This is especially important issue because of the very limited flight time of modern multicopters. The method of determining solutions for Traveling Salesman Problem(TSP), described in this paper bases on Parallel Evolutionary Algorithm (ParEA)with cooperative and independent approach for communication between threads. This method described first by Bożejko and Wodecki [1] bases on the observation that if exists some number of elements on certain positions in a number of permutations which are local minima, then those elements will be in the same position in the optimal solution for TSP problem. Numerical experiments were made on BEM computational cluster with using MPI library.

OPTIMIZATION OF SPECIFIC FUEL CONSUMPTION OF HYDROGEN IN COMMERCIAL TURBOFANS FOR REDUCING GLOBAL WARMING EFFECTS

Energy Technology Data Exchange (ETDEWEB)

T. Hikmet Karakoc; Onder Turan [School of Civil Aviation, Anadolu University, Eskisehir (Turkey)

2008-09-30

The main objective of the present study is to perform minimizing specific fuel consumption of a non afterburning high bypass turbofan engine with separate exhaust streams and unmixed flow for reducing global effect. The values of engine design parameters are optimized for maintaining minimum specific fuel consumption of high bypass turbofan engine under different flight conditions, different fuel types and design criteria. The backbones of optimization approach consisted of elitism-based genetic algorithm coupled with real parametric cycle analysis of a turbofan engine. For solving optimization problem a new software program is developed in MATLAB programming language, while objective function is determined for minimizing the specific fuel consumption. The input variables included the compressor pressure ratio ({pi}{sub c}), bypass ratio ({alpha}) and the fuel heating value [h{sub PR}-(kJ/kg)]. Hydrogen was selected as fuel type in real parametric cycle analysis of commercial turbofans. It may be concluded that the software program developed can successfully solve optimization problems at 10{le}{pi}{sub c}{le}20, 2{le}{alpha}{le}10 and h{sub PR} 120,000 with aircraft flight Mach number {le}0.8.

A Combination of Genetic Algorithm and Particle Swarm Optimization for Vehicle Routing Problem with Time Windows.

Science.gov (United States)

Xu, Sheng-Hua; Liu, Ji-Ping; Zhang, Fu-Hao; Wang, Liang; Sun, Li-Jian

2015-08-27

A combination of genetic algorithm and particle swarm optimization (PSO) for vehicle routing problems with time windows (VRPTW) is proposed in this paper. The improvements of the proposed algorithm include: using the particle real number encoding method to decode the route to alleviate the computation burden, applying a linear decreasing function based on the number of the iterations to provide balance between global and local exploration abilities, and integrating with the crossover operator of genetic algorithm to avoid the premature convergence and the local minimum. The experimental results show that the proposed algorithm is not only more efficient and competitive with other published results but can also obtain more optimal solutions for solving the VRPTW issue. One new well-known solution for this benchmark problem is also outlined in the following.

Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem

Directory of Open Access Journals (Sweden)

Baozhen Yao

2014-02-01

Full Text Available This paper deals with a real-life vehicle delivery routing problem, which is a seafood product delivery routing problem. Considering the features of the seafood product delivery routing problem, this paper formulated this problem as a multi-depot open vehicle routing problem. Since the multi-depot open vehicle routing problem is a very complex problem, a method is used to reduce the complexity of the problem by changing the multi-depot open vehicle routing problem into an open vehicle routing problem with a dummy central depot in this paper. Then, ant colony optimization is used to solve the problem. To improve the performance of the algorithm, crossover operation and some adaptive strategies are used. Finally, the computational results for the benchmark problems of the multi-depot vehicle routing problem indicate that the proposed ant colony optimization is an effective method to solve the multi-depot vehicle routing problem. Furthermore, the computation results of the seafood product delivery problem from Dalian, China also suggest that the proposed ant colony optimization is feasible to solve the seafood product delivery routing problem.

Using VoiceThread to Promote Collaborative Learning in On-Line Clinical Nurse Leader Courses.

Science.gov (United States)

Fox, Ola H

The movement to advance the clinical nurse leader (CNL) as an innovative new role for meeting higher health care quality standards continues with CNL programs offered on-line at colleges and universities nationwide. Collaborative learning activities offer the opportunity for CNL students to gain experience in working together in small groups to negotiate and solve care process problems. The challenge for nurse educators is to provide collaborative learning activities in an asynchronous learning environment that can be considered isolating by default. This article reports on the experiences of 17 CNL students who used VoiceThread, a cloud-based tool that allowed them to communicate asynchronously with one another through voice comments for collaboration and sharing knowledge. Participants identified benefits and drawbacks to using VoiceThread for collaboration as compared to text-based discussion boards. Students reported that the ability to hear the voice of their peers and the instructor helped them feel like they were in a classroom communicating with "real" instructor and peers. Students indicated a preference for on-line classes that used VoiceThread discussions to on-line classes that used only text-based discussion boards. Copyright © 2016 Elsevier Inc. All rights reserved.

VoiceThread as a Peer Review and Dissemination Tool for Undergraduate Research

Science.gov (United States)

Guertin, L. A.

2012-12-01

VoiceThread has been utilized in an undergraduate research methods course for peer review and final research project dissemination. VoiceThread (http://www.voicethread.com) can be considered a social media tool, as it is a web-based technology with the capacity to enable interactive dialogue. VoiceThread is an application that allows a user to place a media collection online containing images, audio, videos, documents, and/or presentations in an interface that facilitates asynchronous communication. Participants in a VoiceThread can be passive viewers of the online content or engaged commenters via text, audio, video, with slide annotations via a doodle tool. The VoiceThread, which runs across browsers and operating systems, can be public or private for viewing and commenting and can be embedded into any website. Although few university students are aware of the VoiceThread platform (only 10% of the students surveyed by Ng (2012)), the 2009 K-12 edition of The Horizon Report (Johnson et al., 2009) lists VoiceThread as a tool to watch because of the opportunities it provides as a collaborative learning environment. In Fall 2011, eleven students enrolled in an undergraduate research methods course at Penn State Brandywine each conducted their own small-scale research project. Upon conclusion of the projects, students were required to create a poster summarizing their work for peer review. To facilitate the peer review process outside of class, each student-created PowerPoint file was placed in a VoiceThread with private access to only the class members and instructor. Each student was assigned to peer review five different student posters (i.e., VoiceThread images) with the audio and doodle tools to comment on formatting, clarity of content, etc. After the peer reviews were complete, the students were allowed to edit their PowerPoint poster files for a new VoiceThread. In the new VoiceThread, students were required to video record themselves describing their research

Problem of detecting inclusions by topological optimization

Directory of Open Access Journals (Sweden)

I. Faye

2014-01-01

Full Text Available In this paper we propose a new method to detect inclusions. The proposed method is based on shape and topological optimization tools. In fact after presenting the problem, we use topologication optimization tools to detect inclusions in the domain. Numerical results are presented.

Gold thread implantation promotes hair growth in human and mice

OpenAIRE

Kim, Jong-Hwan; Cho, Eun-Young; Kwon, Euna; Kim, Woo-Ho; Park, Jin-Sung; Lee, Yong-Soon; Yun, Jun-Won; Kang, Byeong-Cheol

2017-01-01

Thread-embedding therapy has been widely applied for cosmetic purposes such as wrinkle reduction and skin tightening. Particularly, gold thread was reported to support connective tissue regeneration, but, its role in hair biology remains largely unknown due to lack of investigation. When we implanted gold thread and Happy Lift™ in human patient for facial lifting, we unexpectedly found an increase of hair regrowth in spite of no use of hair growth medications. When embedded into the depilated...

Optimal Control Problems for Nonlinear Variational Evolution Inequalities

Directory of Open Access Journals (Sweden)

Eun-Young Ju

2013-01-01

Full Text Available We deal with optimal control problems governed by semilinear parabolic type equations and in particular described by variational inequalities. We will also characterize the optimal controls by giving necessary conditions for optimality by proving the Gâteaux differentiability of solution mapping on control variables.

Optimal recombination in genetic algorithms for combinatorial optimization problems: Part II

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2014-01-01

Full Text Available This paper surveys results on complexity of the optimal recombination problem (ORP, which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. In Part II, we consider the computational complexity of ORPs arising in genetic algorithms for problems on permutations: the Travelling Salesman Problem, the Shortest Hamilton Path Problem and the Makespan Minimization on Single Machine and some other related problems. The analysis indicates that the corresponding ORPs are NP-hard, but solvable by faster algorithms, compared to the problems they are derived from.

A Review of Lightweight Thread Approaches for High Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Castello, Adrian; Pena, Antonio J.; Seo, Sangmin; Mayo, Rafael; Balaji, Pavan; Quintana-Orti, Enrique S.

2016-09-12

High-level, directive-based solutions are becoming the programming models (PMs) of the multi/many-core architectures. Several solutions relying on operating system (OS) threads perfectly work with a moderate number of cores. However, exascale systems will spawn hundreds of thousands of threads in order to exploit their massive parallel architectures and thus conventional OS threads are too heavy for that purpose. Several lightweight thread (LWT) libraries have recently appeared offering lighter mechanisms to tackle massive concurrency. In order to examine the suitability of LWTs in high-level runtimes, we develop a set of microbenchmarks consisting of commonlyfound patterns in current parallel codes. Moreover, we study the semantics offered by some LWT libraries in order to expose the similarities between different LWT application programming interfaces. This study reveals that a reduced set of LWT functions can be sufficient to cover the common parallel code patterns and that those LWT libraries perform better than OS threads-based solutions in cases where task and nested parallelism are becoming more popular with new architectures.

Conversation Threads Hidden within Email Server Logs

Science.gov (United States)

Palus, Sebastian; Kazienko, Przemysław

Email server logs contain records of all email Exchange through this server. Often we would like to analyze those emails not separately but in conversation thread, especially when we need to analyze social network extracted from those email logs. Unfortunately each mail is in different record and those record are not tided to each other in any obvious way. In this paper method for discussion threads extraction was proposed together with experiments on two different data sets - Enron and WrUT..

Kinematics of Planetary Roller Screw Mechanism considering Helical Directions of Screw and Roller Threads

Directory of Open Access Journals (Sweden)

Shangjun Ma

2015-01-01

Full Text Available Based on the differential principle of thread transmission, an analytical model considering helical directions between screw and roller threads in planetary roller screw mechanism (PRSM is presented in this work. The model is critical for the design of PRSM with a smaller lead and a bigger pitch to realize a higher transmission accuracy. The kinematic principle of planetary transmission is employed to analyze the PRSM with different screw thread and roller thread directions. In order to investigate the differences with different screw thread and roller thread directions, the numerical model is developed by using the software Adams to validate the analytical solutions calculated by the presented model. The results indicate, when the helical direction of screw thread is identical with the direction of roller thread, that the lead of PRSM is unaffected regardless of whether sliding between screw and rollers occurs or not. Only when the direction of screw thread is reverse to the direction of roller thread, the design of PRSM with a smaller lead can be realized under a bigger pitch. The presented models and numerical simulation method can be used to research the transmission accuracy of PRSM.

A New Hybrid Whale Optimizer Algorithm with Mean Strategy of Grey Wolf Optimizer for Global Optimization

Directory of Open Access Journals (Sweden)

Narinder Singh

2018-03-01

Full Text Available The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO and Whale Optimizer Algorithm (WOA. We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO algorithm: (i firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.

Optimal control problem for the extended Fisher–Kolmogorov equation

Indian Academy of Sciences (India)

In this paper, the optimal control problem for the extended Fisher–Kolmogorov equation is studied. The optimal control under boundary condition is given, the existence of optimal solution to the equation is proved and the optimality system is established.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Science.gov (United States)

Chen, Wei

2015-07-01

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

On the optimal sizing problem

DEFF Research Database (Denmark)

Vidal, Rene Victor Valqui

1994-01-01

The paper studies the problem of determining the number and dimensions of sizes of apparel so as to maximize profits. It develops a simple one-variable bisection search algorithm that gives the optimal solution. An example is solved interactively using a Macintosh LC and Math CAD, a mathematical...

A new evolutionary algorithm with LQV learning for combinatorial problems optimization

International Nuclear Information System (INIS)

Machado, Marcelo Dornellas; Schirru, Roberto

2000-01-01

Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for combinatorial problems optimization. In this work, a new learning mode, to be used by the population-based incremental learning algorithm, has the aim to build a new evolutionary algorithm to be used in optimization of numerical problems and combinatorial problems. This new learning mode uses a variable learning rate during the optimization process, constituting a process known as proportional reward. The development of this new algorithm aims its application in the optimization of reload problem of PWR nuclear reactors, in order to increase the useful life of the nuclear fuel. For the test, two classes of problems are used: numerical problems and combinatorial problems. Due to the fact that the reload problem is a combinatorial problem, the major interest relies on the last class. The results achieved with the tests indicate the applicability of the new learning mode, showing its potential as a developing tool in the solution of reload problem. (author)

Problem statement for optimal design of steel structures

Directory of Open Access Journals (Sweden)

Ginzburg Aleksandr Vital'evich

2014-07-01

Full Text Available The presented article considers the following complex of tasks. The main stages of the life cycle of a building construction with the indication of process entrance and process exit are described. Requirements imposed on steel constructions are considered. The optimum range of application for steel designs is specified, as well as merits and demerits of a design material. The nomenclature of metal designs is listed - the block diagram is constructed. Possible optimality criteria of steel designs, offered by various authors for various types of constructions are considered. It is established that most often the criterion of a minimum of design mass is accepted as criterion of optimality; more rarely - a minimum of the given expenses, a minimum of a design cost in business. In the present article special attention is paid to a type of objective function of optimization problem. It is also established that depending on the accepted optimality criterion, the use of different types of functions is possible. This complexity of objective function depends on completeness of optimality criterion application. In the work the authors consider the following objective functions: the mass of the main element of a design; objective function by criterion of factory cost; objective function by criterion of cost in business. According to these examples it can be seen that objective functions by the criteria of labor expenses for production of designs are generally non-linear, which complicates solving the optimization problem. Another important factor influencing the problem of optimal design solution for steel designs, which is analyzed, is account for operating restrictions. In the article 8 groups of restrictions are analyzed. Attempts to completely account for the parameters of objective function optimized by particular optimality criteria, taking into account all the operating restrictions, considerably complicates the problem of designing. For solving this

Parallel optimization of IDW interpolation algorithm on multicore platform

Science.gov (United States)

Guan, Xuefeng; Wu, Huayi

2009-10-01

Due to increasing power consumption, heat dissipation, and other physical issues, the architecture of central processing unit (CPU) has been turning to multicore rapidly in recent years. Multicore processor is packaged with multiple processor cores in the same chip, which not only offers increased performance, but also presents significant challenges to application developers. As a matter of fact, in GIS field most of current GIS algorithms were implemented serially and could not best exploit the parallelism potential on such multicore platforms. In this paper, we choose Inverse Distance Weighted spatial interpolation algorithm (IDW) as an example to study how to optimize current serial GIS algorithms on multicore platform in order to maximize performance speedup. With the help of OpenMP, threading methodology is introduced to split and share the whole interpolation work among processor cores. After parallel optimization, execution time of interpolation algorithm is greatly reduced and good performance speedup is achieved. For example, performance speedup on Intel Xeon 5310 is 1.943 with 2 execution threads and 3.695 with 4 execution threads respectively. An additional output comparison between pre-optimization and post-optimization is carried out and shows that parallel optimization does to affect final interpolation result.

ABCluster: the artificial bee colony algorithm for cluster global optimization.

Science.gov (United States)

Zhang, Jun; Dolg, Michael

2015-10-07

Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

A Risk-Sensitive Portfolio Optimization Problem with Fixed Incomes Securities

OpenAIRE

Goel, Mayank; Kumar, K. Suresh

2007-01-01

We discuss a class of risk-sensitive portfolio optimization problems. We consider the portfolio optimization model investigated by Nagai in 2003. The model by its nature can include fixed income securities as well in the portfolio. Under fairly general conditions, we prove the existence of optimal portfolio in both finite and infinite horizon problems.

A hybrid iterative scheme for optimal control problems governed by ...

African Journals Online (AJOL)

MRT

KEY WORDS: Optimal control problem; Fredholm integral equation; ... control problems governed by Fredholm integral and integro-differential equations is given in (Brunner and Yan, ..... The exact optimal trajectory and control functions are. 2.

Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers

Energy Technology Data Exchange (ETDEWEB)

Sarje, Abhinav [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jacobsen, Douglas W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Samuel W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ringler, Todd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-05-01

The incorporation of increasing core counts in modern processors used to build state-of-the-art supercomputers is driving application development towards exploitation of thread parallelism, in addition to distributed memory parallelism, with the goal of delivering efficient high-performance codes. In this work we describe the exploitation of threading and our experiences with it with respect to a real-world ocean modeling application code, MPAS-Ocean. We present detailed performance analysis and comparisons of various approaches and configurations for threading on the Cray XC series supercomputers.

Statistical physics of hard optimization problems

International Nuclear Information System (INIS)

Zdeborova, L.

2009-01-01

Optimization is fundamental in many areas of science, from computer science and information theory to engineering and statistical physics, as well as to biology or social sciences. It typically involves a large number of variables and a cost function depending on these variables. Optimization problems in the non-deterministic polynomial (NP)-complete class are particularly difficult, it is believed that the number of operations required to minimize the cost function is in the most difficult cases exponential in the system size. However, even in an NP-complete problem the practically arising instances might, in fact, be easy to solve. The principal question we address in this article is: How to recognize if an NP-complete constraint satisfaction problem is typically hard and what are the main reasons for this? We adopt approaches from the statistical physics of disordered systems, in particular the cavity method developed originally to describe glassy systems. We describe new properties of the space of solutions in two of the most studied constraint satisfaction problems - random satisfy ability and random graph coloring. We suggest a relation between the existence of the so-called frozen variables and the algorithmic hardness of a problem. Based on these insights, we introduce a new class of problems which we named ”locked” constraint satisfaction, where the statistical description is easily solvable, but from the algorithmic point of view they are even more challenging than the canonical satisfy ability.

Statistical physics of hard optimization problems

International Nuclear Information System (INIS)

Zdeborova, L.

2009-01-01

Optimization is fundamental in many areas of science, from computer science and information theory to engineering and statistical physics, as well as to biology or social sciences. It typically involves a large number of variables and a cost function depending on these variables. Optimization problems in the non-deterministic polynomial-complete class are particularly difficult, it is believed that the number of operations required to minimize the cost function is in the most difficult cases exponential in the system size. However, even in an non-deterministic polynomial-complete problem the practically arising instances might, in fact, be easy to solve. The principal the question we address in the article is: How to recognize if an non-deterministic polynomial-complete constraint satisfaction problem is typically hard and what are the main reasons for this? We adopt approaches from the statistical physics of disordered systems, in particular the cavity method developed originally to describe glassy systems. We describe new properties of the space of solutions in two of the most studied constraint satisfaction problems - random satisfiability and random graph coloring. We suggest a relation between the existence of the so-called frozen variables and the algorithmic hardness of a problem. Based on these insights, we introduce a new class of problems which we named 'locked' constraint satisfaction, where the statistical description is easily solvable, but from the algorithmic point of view they are even more challenging than the canonical satisfiability (Authors)

Statistical physics of hard optimization problems

Science.gov (United States)

Zdeborová, Lenka

2009-06-01

Optimization is fundamental in many areas of science, from computer science and information theory to engineering and statistical physics, as well as to biology or social sciences. It typically involves a large number of variables and a cost function depending on these variables. Optimization problems in the non-deterministic polynomial (NP)-complete class are particularly difficult, it is believed that the number of operations required to minimize the cost function is in the most difficult cases exponential in the system size. However, even in an NP-complete problem the practically arising instances might, in fact, be easy to solve. The principal question we address in this article is: How to recognize if an NP-complete constraint satisfaction problem is typically hard and what are the main reasons for this? We adopt approaches from the statistical physics of disordered systems, in particular the cavity method developed originally to describe glassy systems. We describe new properties of the space of solutions in two of the most studied constraint satisfaction problems - random satisfiability and random graph coloring. We suggest a relation between the existence of the so-called frozen variables and the algorithmic hardness of a problem. Based on these insights, we introduce a new class of problems which we named "locked" constraint satisfaction, where the statistical description is easily solvable, but from the algorithmic point of view they are even more challenging than the canonical satisfiability.

Truss topology optimization with discrete design variables by outer approximation

DEFF Research Database (Denmark)

Stolpe, Mathias

2015-01-01

Several variants of an outer approximation method are proposed to solve truss topology optimization problems with discrete design variables to proven global optimality. The objective is to minimize the volume of the structure while satisfying constraints on the global stiffness of the structure...... for classical outer approximation approaches applied to optimal design problems. A set of two- and three-dimensional benchmark problems are solved and the numerical results suggest that the proposed approaches are competitive with other special-purpose global optimization methods for the considered class...... under the applied loads. We extend the natural problem formulation by adding redundant force variables and force equilibrium constraints. This guarantees that the designs suggested by the relaxed master problems are capable of carrying the applied loads, a property which is generally not satisfied...

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

Science.gov (United States)

Vaziri Yazdi Pin, Mohammad

practices. Single criterion optimization algorithms using mathematical programming for globally optimal solutions have been developed for three objectives of cost, reliability, and the social/environmental impacts. Additional algorithms for inclusions of upgrade and optimal load assignment possibilities have been developed. Algorithms have been developed to handle the expansion as a multiobjective decision process. Typical data from both major investor owned and major municipal utilities operating in California USA, have been utilized to implement and test the algorithms on practical test cases. Results of the case studies and associated analyses indicate that the developed algorithms also perform efficiently in solving the multistage and multiobjective expansion problem.

Argobots: A Lightweight Low-Level Threading and Tasking Framework

Energy Technology Data Exchange (ETDEWEB)

Seo, Sangmin; Amer, Abdelhalim; Balaji, Pavan; Bordage, Cyril; Bosilca, George; Brooks, Alex; Carns, Philip; Castello, Adrian; Genet, Damien; Herault, Thomas; Iwasaki, Shintaro; Jindal, Prateek; Kale, Laxmikant V.; Krishnamoorthy, Sriram; Lifflander, Jonathan; Lu, Huiwei; Meneses, Esteban; Snir, Marc; Sun, Yanhua; Taura, Kenjiro; Beckman, Pete

2018-03-01

In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, either are too specific to applications or architectures or are not as powerful or flexible. In this paper, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by end users or high-level programming models. We describe the design, implementation, and performance characterization of Argobots and present integrations with three high-level models: OpenMP, MPI, and colocated I/O services. Evaluations show that (1) Argobots, while providing richer capabilities, is competitive with existing simpler generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency-hiding capabilities; and (4) I/O services with Argobots reduce interference with colocated applications while achieving performance competitive with that of a Pthreads approach.

X-ray measurement of residual stress on bolt threads

International Nuclear Information System (INIS)

Hagiwara, Masaya; Nakahara, Kanefumi; Yoshimoto, Isamu.

1989-01-01

This study deals with X-ray measurement of residual stress at the local area around the thread root of a bolt. Residual stress in the 0.5 mm x 5 mm area was measured using a method of stepped scanning and parabolic approximation. The conditions of measurement had been determined and evaluated through the preliminary measurement of compressive stress acting on the cylindrical surface. Furthermore, the fatigue strength estimated by applying the residual stress data to the previously presented hypothesis was compared with the experimental results. The main conclusions obtained were as follows: (1) The residual stress in a relatively small area on the cylindrical surface with large curvature can be measured by X-ray using a method of stepped scanning and parabolic approximation; (2) The compressive residual stress measured at the thread root was larger for the bolt manufactured by thread rolling after heat treatment than for one manufactured by thread rolling before heat treatment; (3) The distribution of residual stress along the axial direction from the thread root to the portion under crest did not represent remarkable change in its value; (4) The residual stress of a bolt was somewhat decreased by fatigue loading on the condition of low mean stress; (5) The fatigue strength estimated using residual stress data showed the tendency of experimental results well. (author)

Theory and Algorithms for Global/Local Design Optimization

National Research Council Canada - National Science Library

Watson, Layne T; Guerdal, Zafer; Haftka, Raphael T

2005-01-01

The motivating application for this research is the global/local optimal design of composite aircraft structures such as wings and fuselages, but the theory and algorithms are more widely applicable...

Geant4-MT: bringing multi-threading into Geant4 production

International Nuclear Information System (INIS)

Ahn, S.; Apostolakis, J.; Cosmo, G.; Nowak, A.; Asai, M.; Brandt, D.; Dotti, A.; Coopermann, G.; Dong, X.; Jun, Soon Yung

2013-01-01

Geant4-MT is the multi-threaded version of the Geant4 particle transport code. The key goals for the design of Geant4-MT have been a) the need to reduce the memory footprint of the multi-threaded application compared to the use of separate jobs and processes; b) to create an easy migration of the existing applications; and c) to use efficiently many threads or cores, by scaling up to tens and potentially hundreds of workers. The first public release of a Geant4- MT prototype was made in 2011. We report on the revision of Geant4-MT for inclusion in the production-level release scheduled for end of 2013. This has involved significant re-engineering of the prototype in order to incorporate it into the main Geant4 development line, and the porting of Geant4-MT threading code to additional platforms. In order to make the porting of applications as simple as possible, refinements addressed the needs of standalone applications. Further adaptations were created to improve the fit with the frameworks of High Energy Physics experiments. We report on performances measurements on Intel Xeon TM , AMD Opteron TM the first trials of Geant4-MT on the Intel Many Integrated Cores (MIC) architecture, in the form of the Xeon Phi TM co-processor. These indicate near-linear scaling through about 200 threads on 60 cores, when holding fixed the number of events per thread. (authors)

The core of the global warming problem: energy

International Nuclear Information System (INIS)

Hu, E.

2005-01-01

From the thermodynamic point of view, the global warming problem is an 'energy balance' problem. The heat (energy) accumulation in the earth and its atmosphere is the cause of global warming. This accumulation is mainly due to the imbalance of (solar) energy reaching and the energy leaving the earth, caused by 'greenhouse effect' in which the CO 2 and other greenhouse gases play a critical role; so that balance of the energy entering and leaving the earth should be the key to solve the problem. Currently in the battle of tackling the global warming, we mainly focus on the development of CO 2 -related measures, i.e., emission reduction, CO 2 sequestration, and CO 2 recycle technologies. It is right in technical aspect, because they are attempting to thin the CO 2 'blanket' around the earth. However, 'Energy' that is the core of the problem has been overlooked, at least in management/policy aspect. This paper is proposing an 'Energy Credit' i.e., the energy measure concept as an alternative to the 'CO 2 credit' that is currently in place in the proposed emission trading scheme. The proposed energy credit concept has the advantages such as covering broad activities related to the global warming and not just direct emissions. Three examples are given in the paper to demonstrate the concept of the energy measure and its advantages over the CO 2 credit concept. (Author)

Mechanical Strength Improvements of Carbon Nanotube Threads through Epoxy Cross-Linking

Directory of Open Access Journals (Sweden)

Qingyue Yu

2016-01-01

Full Text Available Individual Carbon Nanotubes (CNTs have a great mechanical strength that needs to be transferred into macroscopic fiber assemblies. One approach to improve the mechanical strength of the CNT assemblies is by creating covalent bonding among their individual CNT building blocks. Chemical cross-linking of multiwall CNTs (MWCNTs within the fiber has significantly improved the strength of MWCNT thread. Results reported in this work show that the cross-linked thread had a tensile strength six times greater than the strength of its control counterpart, a pristine MWCNT thread (1192 MPa and 194 MPa, respectively. Additionally, electrical conductivity changes were observed, revealing 2123.40 S·cm−1 for cross-linked thread, and 3984.26 S·cm−1 for pristine CNT thread. Characterization suggests that the obtained high tensile strength is due to the cross-linking reaction of amine groups from ethylenediamine plasma-functionalized CNT with the epoxy groups of the cross-linking agent, 4,4-methylenebis(N,N-diglycidylaniline.

Adjusting process count on demand for petascale global optimization

KAUST Repository

Sosonkina, Masha; Watson, Layne T.; Radcliffe, Nicholas R.; Haftka, Rafael T.; Trosset, Michael W.

2013-01-01

There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running at the petascale are likely to be memory intensive, which makes thrashing a serious problem for many petascale applications. One way to overcome this challenge is to use a dynamic number of processes, so that the total amount of memory available for the computation can be increased on demand. This paper describes modifications made to the massively parallel global optimization code pVTdirect in order to allow for a dynamic number of processes. In particular, the modified version of the code monitors memory use and spawns new processes if the amount of available memory is determined to be insufficient. The primary design challenges are discussed, and performance results are presented and analyzed.