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Author: Christodoulos A. Floudas
Publisher: Springer Science & Business Media
ISBN: 1461334373
Category : Mathematics
Languages : en
Pages : 638
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Book Description
Optimization problems abound in most fields of science, engineering, and tech nology. 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 solving large classes of problems from diverse areas such as engineering design and control, computational chemistry and biology, structural optimization, computer science, operations research, and economics. This book contains refereed invited papers presented at the conference on "State of the Art in Global Optimization: Computational Methods and Applications" held at Princeton University, April 28-30, 1995. The conference presented current re search on global optimization and related applications in science and engineering. The papers included in this book cover a wide spectrum of approaches for solving global optimization problems and applications.
Author: Christodoulos A. Floudas
Publisher: Springer Science & Business Media
ISBN: 1461334373
Category : Mathematics
Languages : en
Pages : 638
Get Book Here
Book Description
Optimization problems abound in most fields of science, engineering, and tech nology. 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 solving large classes of problems from diverse areas such as engineering design and control, computational chemistry and biology, structural optimization, computer science, operations research, and economics. This book contains refereed invited papers presented at the conference on "State of the Art in Global Optimization: Computational Methods and Applications" held at Princeton University, April 28-30, 1995. The conference presented current re search on global optimization and related applications in science and engineering. The papers included in this book cover a wide spectrum of approaches for solving global optimization problems and applications.
Author: Pascal Van Hentenryck
Publisher: MIT Press
ISBN: 9780262720274
Category : Biography & Autobiography
Languages : en
Pages : 236
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Book Description
Many science and engineering applications require the user to find solutions to systems of nonlinear constraints or to optimize a nonlinear function subject to nonlinear constraints. The field of global optimization is the study of methods to find all solutions to systems of nonlinear constraints and all global optima to optimization problems. Numerica is modeling language for global optimization that makes it possible to state nonlinear problems in a form close to the statements traditionally found in textbooks and scientific papers. The constraint-solving algorithm of Numerica is based on a combination of traditional numerical methods such as interval and local methods, and constraint satisfaction techniques. This comprehensive presentation of Numerica describes its design, functions, and implementation. It also discusses how to use Numerica effectively to solve practical problems and reports a number of experimental results. A commercial implementation of Numerica is available from ILOG under the name ILOG Numerica.
Author: Nadia Creignou
Publisher: SIAM
ISBN: 0898714796
Category : Mathematics
Languages : en
Pages : 112
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Book Description
Presents a novel form of a compendium that classifies an infinite number of problems by using a rule-based approach.
Author: Pascal Van Hentenryck
Publisher: MIT Press (MA)
ISBN:
Category : Constraint programming (Computer science).
Languages : en
Pages : 250
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Book Description
This book tackles classic problems from operations research and circuit design using a logic programming language embedding consistency techniques, a paradigm emerging from artificial intelligence research. Van Hentenryck proposes a new approach to solving discrete combinatorial problems using these techniques.Logic programming serves as a convenient language for stating combinatorial problems, but its "generate and test" paradigm leads to inefficient programs. Van Hentenryck's approach preserves one of the most useful features of logic programming - the duality of its semantics - yet allows a short development time for the programs while preserving most of the efficiency of special purpose programs written in a procedural language.Embedding consistency techniques in logic programming allows for ease and flexibility of programming and short development time because constraint propagation and tree-search programming are abstracted away from the user. It also enables logic programs to be executed efficiently as consistency techniques permit an active use of constraints to remove combinations of values that cannot appear in a solution Van Hentenryck presents a comprehensive overview of this new approach from its theoretical foundations to its design and implementation, including applications to real life combinatorial problems.The ideas introduced in "Constraint Satisfaction in Logic Programming "have been used successfully to solve more than a dozen practical problems in operations research and circuit design, including disjunctive scheduling, warehouse location, cutting stock car sequencing, and microcode labeling problems.Pascal Van Hentenryck is a member of the research staff at the European Computer Industry Research Centre. "Constraint Satisfaction in Logic Programming" is based on research for the Centre's CHIP project. As an outgrowth of this project, a new language (CHIP) that will include consistency techniques has been developed for commercial use. The book is included in the Logic Programming series edited by Ehud Shapiro.
Author: John N. Hooker
Publisher: Springer Science & Business Media
ISBN: 146141900X
Category : Business & Economics
Languages : en
Pages : 655
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Book Description
The first edition of Integrated Methods for Optimization was published in January 2007. Because the book covers a rapidly developing field, the time is right for a second edition. The book provides a unified treatment of optimization methods. It brings ideas from mathematical programming (MP), constraint programming (CP), and global optimization (GO)into a single volume. There is no reason these must be learned as separate fields, as they normally are, and there are three reasons they should be studied together. (1) There is much in common among them intellectually, and to a large degree they can be understood as special cases of a single underlying solution technology. (2) A growing literature reports how they can be profitably integrated to formulate and solve a wide range of problems. (3) Several software packages now incorporate techniques from two or more of these fields. The book provides a unique resource for graduate students and practitioners who want a well-rounded background in optimization methods within a single course of study. Engineering students are a particularly large potential audience, because engineering optimization problems often benefit from a combined approach—particularly where design, scheduling, or logistics are involved. The text is also of value to those studying operations research, because their educational programs rarely cover CP, and to those studying computer science and artificial intelligence (AI), because their curric ula typically omit MP and GO. The text is also useful for practitioners in any of these areas who want to learn about another, because it provides a more concise and accessible treatment than other texts. The book can cover so wide a range of material because it focuses on ideas that arerelevant to the methods used in general-purpose optimization and constraint solvers. The book focuses on ideas behind the methods that have proved useful in general-purpose optimization and constraint solvers, as well as integrated solvers of the present and foreseeable future. The second edition updates results in this area and includes several major new topics: Background material in linear, nonlinear, and dynamic programming. Network flow theory, due to its importance in filtering algorithms. A chapter on generalized duality theory that more explicitly develops a unifying primal-dual algorithmic structure for optimization methods. An extensive survey of search methods from both MP and AI, using the primal-dual framework as an organizing principle. Coverage of several additional global constraints used in CP solvers. The book continues to focus on exact as opposed to heuristic methods. It is possible to bring heuristic methods into the unifying scheme described in the book, and the new edition will retain the brief discussion of how this might be done.
Author: Krzysztof Apt
Publisher: Cambridge University Press
ISBN: 1139438700
Category : Computers
Languages : en
Pages : 421
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Book Description
Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list of references will also be valuable to professionals in computer science and artificial intelligence.
Author: Aimo Törn
Publisher: Springer Science & Business Media
ISBN: 0387367217
Category : Mathematics
Languages : en
Pages : 362
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Book Description
The research of Antanas Zilinskas has focused on developing models for global optimization, implementing and investigating the corresponding algorithms, and applying those algorithms to practical problems. This volume, dedicated to Professor Zilinskas on the occasion of his 60th birthday, contains new survey papers in which leading researchers from the field present various models and algorithms for solving global optimization problems.
Author: Khaled Ghedira
Publisher: John Wiley & Sons
ISBN: 1118575016
Category : Mathematics
Languages : en
Pages : 245
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Book Description
A Constraint Satisfaction Problem (CSP) consists of a set of variables, a domain of values for each variable and a set of constraints. The objective is to assign a value for each variable such that all constraints are satisfied. CSPs continue to receive increased attention because of both their high complexity and their omnipresence in academic, industrial and even real-life problems. This is why they are the subject of intense research in both artificial intelligence and operations research. This book introduces the classic CSP and details several extensions/improvements of both formalisms and techniques in order to tackle a large variety of problems. Consistency, flexible, dynamic, distributed and learning aspects are discussed and illustrated using simple examples such as the n-queen problem. Contents 1. Foundations of CSP. 2. Consistency Reinforcement Techniques. 3. CSP Solving Algorithms. 4. Search Heuristics. 5. Learning Techniques. 6. Maximal Constraint Satisfaction Problems. 7. Constraint Satisfaction and Optimization Problems. 8. Distibuted Constraint Satisfaction Problems. About the Authors Khaled Ghedira is the general managing director of the Tunis Science City in Tunisia, Professor at the University of Tunis, as well as the founding president of the Tunisian Association of Artificial Intelligence and the founding director of the SOIE research laboratory. His research areas include MAS, CSP, transport and production logistics, metaheuristics and security in M/E-government. He has led several national and international research projects, supervised 30 PhD theses and more than 50 Master’s theses, co-authored about 300 journal, conference and book research papers, written two text books on metaheuristics and production logistics and co-authored three others.
Author: Gade Pandu Rangaiah
Publisher: World Scientific
ISBN: 9814299219
Category : Computers
Languages : en
Pages : 722
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Book Description
Ch. 1. Introduction / Gade Pandu Rangaiah -- ch. 2. Formulation and illustration of Luus-Jaakola optimization procedure / Rein Luus -- ch. 3. Adaptive random search and simulated annealing optimizers : algorithms and application issues / Jacek M. Jezowski, Grzegorz Poplewski and Roman Bochenek -- ch. 4. Genetic algorithms in process engineering : developments and implementation issues / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 5. Tabu search for global optimization of problems having continuous variables / Sim Mong Kai, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 6. Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. Jayaraman [und weitere] -- ch. 8. Particle swarm optimization for solving NLP and MINLP in chemical engineering / Bassem Jarboui [und weitere] -- ch. 9. An introduction to the harmony search algorithm / Gordon Ingram and Tonghua Zhang -- ch. 10. Meta-heuristics : evaluation and reporting techniques / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 11. A hybrid approach for constraint handling in MINLP optimization using stochastic algorithms / G.A. Durand [und weitere] -- ch. 12. Application of Luus-Jaakola optimization procedure to model reduction, parameter estimation and optimal control / Rein Luus -- ch. 13. Phase stability and equilibrium calculations in reactive systems using differential evolution and tabu search / Adrian Bonilla-Petriciolet [und weitere] -- ch. 14. Differential evolution with tabu list for global optimization : evaluation of two versions on benchmark and phase stability problems / Mekapati Srinivas and Gade Pandu Rangaiah -- ch. 15. Application of adaptive random search optimization for solving industrial water allocation problem / Grzegorz Poplewski and Jacek M. Jezowski -- ch. 16. Genetic algorithms formulation for retrofitting heat exchanger network / Roman Bochenek and Jacek M. Jezowski -- ch. 17. Ant colony optimization for classification and feature selection / V.K. Jayaraman [und weitere] -- ch. 18. Constraint programming and genetic algorithm / Prakash R. Kotecha, Mani Bhushan and Ravindra D. Gudi -- ch. 19. Schemes and implementations of parallel stochastic optimization algorithms application of tabu search to chemical engineering problems / B. Lin and D.C. Miller
Author: Francesca Rossi
Publisher: Elsevier
ISBN: 0080463800
Category : Computers
Languages : en
Pages : 977
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Book Description
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics.The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area.The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming.- Covers the whole field of constraint programming- Survey-style chapters- Five chapters on applications
