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Theoretical Computer Science and General Issues

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

International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings

Editors: Stützle, Thomas, Birattari, Mauro, Hoos, Holger H. (Eds.)

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  • Presents the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms
  • Includes twelve full papers and nine short papers
  • Covers methodological developments, behavior of SLS algorithms, search space analysis, algorithm performance, tuning procedures, AI/OR techniques, and dynamic behavior
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About this book

Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. To a large degree, this popularity is based on the conceptual simplicity of many SLS methods and on their excellent performance on a wide gamut of problems, ranging from rather abstract problems of high academic interest to the very s- ci?c problems encountered in many real-world applications. SLS methods range from quite simple construction procedures and iterative improvement algorithms to more complex general-purpose schemes, also widely known as metaheuristics, 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, and overall resembled more an art than a science. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-speci?c background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.

Table of contents (21 chapters)

Table of contents (21 chapters)

Buy this book

eBook $59.99
price for USA in USD
  • ISBN 978-3-540-74446-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $79.99
price for USA in USD
  • ISBN 978-3-540-74445-0
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Book Subtitle
International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings
Editors
  • Thomas Stützle
  • Mauro Birattari
  • Holger H. Hoos
Series Title
Theoretical Computer Science and General Issues
Series Volume
4638
Copyright
2007
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-74446-7
DOI
10.1007/978-3-540-74446-7
Softcover ISBN
978-3-540-74445-0
Edition Number
1
Number of Pages
X, 230
Topics

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