Stochastic Search Algorithms
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Stochastic Local Search Algorithms For Multiobjective Combinatorial Optimization
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Author : Luis F. Paquete
language : de
Publisher: IOS Press
Release Date : 2006
Stochastic Local Search Algorithms For Multiobjective Combinatorial Optimization written by Luis F. Paquete and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
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."
Stochastic Local Search
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Author : Holger H. Hoos
language : en
Publisher: Elsevier
Release Date : 2004-09-28
Stochastic Local Search written by Holger H. Hoos and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-28 with Computers categories.
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. Provides the first unified view of the field Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms
Stochastic Search Algorithms
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Author : Holger H. Hoos
language : en
Publisher:
Release Date : 2007
Stochastic Search Algorithms written by Holger H. Hoos and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computer algorithms categories.
Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics
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Author : Thomas Stützle
language : en
Publisher: Springer
Release Date : 2007-08-22
Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics written by Thomas Stützle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-22 with Computers categories.
This volume constitutes the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms. Inside the volume, readers will find twelve full papers as well as nine short papers. Topics include methodological developments, behavior of SLS algorithms, search space analysis, algorithm performance, tuning procedures, AI/OR techniques, and dynamic behavior.
Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics
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Author : Thomas Stützle
language : en
Publisher: Springer
Release Date : 2009-09-01
Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics written by Thomas Stützle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-01 with Computers categories.
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.
Stochastic Algorithms Foundations And Applications
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Author : Andreas Albrecht
language : en
Publisher: Springer
Release Date : 2003-11-20
Stochastic Algorithms Foundations And Applications written by Andreas Albrecht and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-11-20 with Mathematics categories.
This book constitutes the refereed proceedings of the Second International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2003, held in Hatfield, UK in September 2003. The 12 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the book. Among the topics addressed are ant colony optimization, randomized algorithms for the intersection problem, local search for constraint satisfaction problems, randomized local search and combinatorial optimization, simulated annealing, probabilistic global search, network communication complexity, open shop scheduling, aircraft routing, traffic control, randomized straight-line programs, and stochastic automata and probabilistic transformations.
Stochastic Adaptive Search For Global Optimization
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Author : Z.B. Zabinsky
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-27
Stochastic Adaptive Search For Global Optimization written by Z.B. Zabinsky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-27 with Mathematics categories.
The field of global optimization has been developing at a rapid pace. There is a journal devoted to the topic, as well as many publications and notable books discussing various aspects of global optimization. This book is intended to complement these other publications with a focus on stochastic methods for global optimization. Stochastic methods, such as simulated annealing and genetic algo rithms, are gaining in popularity among practitioners and engineers be they are relatively easy to program on a computer and may be cause applied to a broad class of global optimization problems. However, the theoretical performance of these stochastic methods is not well under stood. In this book, an attempt is made to describe the theoretical prop erties of several stochastic adaptive search methods. Such a theoretical understanding may allow us to better predict algorithm performance and ultimately design new and improved algorithms. This book consolidates a collection of papers on the analysis and de velopment of stochastic adaptive search. The first chapter introduces random search algorithms. Chapters 2-5 describe the theoretical anal ysis of a progression of algorithms. A main result is that the expected number of iterations for pure adaptive search is linear in dimension for a class of Lipschitz global optimization problems. Chapter 6 discusses algorithms, based on the Hit-and-Run sampling method, that have been developed to approximate the ideal performance of pure random search. The final chapter discusses several applications in engineering that use stochastic adaptive search methods.
Stochastic Local Search Methods Models Applications
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Author : Holger Hoos
language : en
Publisher: IOS Press
Release Date : 1999
Stochastic Local Search Methods Models Applications written by Holger Hoos and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
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).
Stochastic Local Search Algorithms For Multiobjective Combinatorial Optimization
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Author : Luís F. Paquete
language : en
Publisher:
Release Date : 2006
Stochastic Local Search Algorithms For Multiobjective Combinatorial Optimization written by Luís F. Paquete and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Combinatorial optimization categories.
Bioinspired Computation In Combinatorial Optimization
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Author : Frank Neumann
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-04
Bioinspired Computation In Combinatorial Optimization written by Frank Neumann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-04 with Mathematics categories.
Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.