Stochastic Local Search

Stochastic Local Search PDF Author: Holger H. Hoos
Publisher: Morgan Kaufmann
ISBN: 1558608729
Category : Business & Economics
Languages : en
Pages : 678

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Book Description
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Stochastic Local Search

Stochastic Local Search PDF Author: Holger H. Hoos
Publisher: Morgan Kaufmann
ISBN: 1558608729
Category : Business & Economics
Languages : en
Pages : 678

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Book Description
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Stochastic Local Search - Methods, Models, Applications

Stochastic Local Search - Methods, Models, Applications PDF Author: Holger Hoos
Publisher: IOS Press
ISBN: 9781586031169
Category : Mathematics
Languages : en
Pages : 236

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Book Description
To date, stochastic local search (SLS) algorithms are among the standard methods for solving hard combinatorial problems from various areas of Artificial Intelligence and Operations Research. Some of the most successful and powerful algorithms for prominent problems like SAT, CSP, or TSP are based on stochastic local search. This work investigates various aspects of SLS algorithms; in particular, it focusses on modelling these algorithms, empirically evaluating their performance, characterising and improving their behaviour, and understanding the factors which influence their efficiency. These issues are studied for the SAT problem in propositional logic as a primary application domain. SAT has the advantage of being conceptually very simple, which facilitates the design, implementation, and presentation of algorithms as well as their analysis. However, most of the methodology generalises easily to other combinatorial problems like CSP. This Ph.D. thesis won the Best Dissertation Award 1999 (Dissertationspreis) of the German Informatics Society (Gesellschaft fur Informatik).

DNA Computing

DNA Computing PDF Author: Masami Hagiya
Publisher: Springer Science & Business Media
ISBN: 3540005315
Category : Computers
Languages : en
Pages : 352

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Book Description
This book constitutes the thoroughly refereed post-proceedings of the 8th International Workshop on DNA Based Computers, DNA8, held in Sapporo, Japan, in June 2002. The 30 revised full papers presented were carefully selected during two rounds of reviewing and improvement from an initial total of 68 submissions. The papers are organized in topical sections on self-assembly and autonomous molecular computation, molecular evolution and application to biotechnology, applications to mathematical problems, nucleic acid sequence design, and theory.

Handbook of Heuristics

Handbook of Heuristics PDF Author: Rafael Martí
Publisher: Springer
ISBN: 9783319071237
Category : Computers
Languages : en
Pages : 3000

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Book Description
Heuristics are strategies using readily accessible, loosely applicable information to control problem solving. Algorithms, for example, are a type of heuristic. By contrast, Metaheuristics are methods used to design Heuristics and may coordinate the usage of several Heuristics toward the formulation of a single method. GRASP (Greedy Randomized Adaptive Search Procedures) is an example of a Metaheuristic. To the layman, heuristics may be thought of as ‘rules of thumb’ but despite its imprecision, heuristics is a very rich field that refers to experience-based techniques for problem-solving, learning, and discovery. Any given solution/heuristic is not guaranteed to be optimal but heuristic methodologies are used to speed up the process of finding satisfactory solutions where optimal solutions are impractical. The introduction to this Handbook provides an overview of the history of Heuristics along with main issues regarding the methodologies covered. This is followed by Chapters containing various examples of local searches, search strategies and Metaheuristics, leading to an analyses of Heuristics and search algorithms. The reference concludes with numerous illustrations of the highly applicable nature and implementation of Heuristics in our daily life. Each chapter of this work includes an abstract/introduction with a short description of the methodology. Key words are also necessary as part of top-matter to each chapter to enable maximum search engine optimization. Next, chapters will include discussion of the adaptation of this methodology to solve a difficult optimization problem, and experiments on a set of representative problems.

Local Search in Combinatorial Optimization

Local Search in Combinatorial Optimization PDF Author: Emile H. L. Aarts
Publisher: Princeton University Press
ISBN: 9780691115221
Category : Computers
Languages : en
Pages : 530

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Book Description
1. Introduction -- 2. Computational complexity -- 3. Local improvement on discrete structures -- 4. Simulated annealing -- 5. Tabu search -- 6. Genetic algorithms -- 7. Artificial neural networks -- 8. The traveling salesman problem: A case study -- 9. Vehicle routing: Modern heuristics -- 10. Vehicle routing: Handling edge exchanges -- 11. Machine scheduling -- 12. VLSI layout synthesis -- 13. Code design.

Local Search Algorithms for Combinatorial Problems

Local Search Algorithms for Combinatorial Problems PDF Author: Thomas G. Stützle
Publisher:
ISBN: 9783896012203
Category :
Languages : en
Pages : 203

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Book Description


Handbook of Satisfiability

Handbook of Satisfiability PDF Author: A. Biere
Publisher: IOS Press
ISBN: 1643681613
Category : Computers
Languages : en
Pages : 1486

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Book Description
Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"

Theory and Applications of Satisfiability Testing

Theory and Applications of Satisfiability Testing PDF Author: Enrico Giunchiglia
Publisher: Springer Science & Business Media
ISBN: 3540208518
Category : Computers
Languages : en
Pages : 542

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Book Description
This book constitutes the thoroughly refereed post-proceedings of the 6th International Conference on Theory and Applications of Satisfiability Testing, SAT 2003, held in Santa Margherita Ligure, Italy, in May 2003. The 33 revised full papers presented together with 5 articles reporting results of the related SAT competition and QBF evaluation were carefully selected during two rounds of reviewing and improvement from 67 submissions. The whole spectrum of research in propositional and quantified Boolean formula satisfiability testing is covered including proof systems, search techniques, probabilistic analysis of algorithms and their properties, problem encodings, industrial applications, specific tools, case studies, and empirical results.

Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization

Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimization PDF Author: Luis F. Paquete
Publisher: IOS Press
ISBN: 9781586035969
Category : Business & Economics
Languages : en
Pages : 394

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Book Description
Stochastic Local Search algorithms were shown to give state-of-the-art results for many other problems, but little is known on how to design and analyse them for Multiobjective Combinatorial Optimization Problems. This book aims to fill this gap. It defines two search models that correspond to two distinct ways of tackling MCOPs by SLS algorithms."

Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics

Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics PDF Author: Thomas Stützle
Publisher: Springer
ISBN: 3642037518
Category : Computers
Languages : en
Pages : 165

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Book Description
Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics.