Overview
- Comprehensive introduction to principles of reactive search
- Focuses on methods, but uses problems to help demonstrate points
- Important reading for anyone in decision science within areas of business, engineering, economics, or science
Part of the book series: Operations Research/Computer Science Interfaces Series (ORCS, volume 45)
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Table of contents (13 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics.
Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities forthe automated tuning of these parameters.
Authors and Affiliations
Bibliographic Information
Book Title: Reactive Search and Intelligent Optimization
Authors: Roberto Battiti, Mauro Brunato, Franco Mascia
Series Title: Operations Research/Computer Science Interfaces Series
DOI: https://doi.org/10.1007/978-0-387-09624-7
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2009
Hardcover ISBN: 978-0-387-09623-0Published: 06 November 2008
Softcover ISBN: 978-1-4419-3499-4Published: 06 December 2010
eBook ISBN: 978-0-387-09624-7Published: 16 December 2008
Series ISSN: 1387-666X
Series E-ISSN: 2698-5489
Edition Number: 1
Number of Pages: X, 196
Number of Illustrations: 74 b/w illustrations
Topics: Operations Research, Management Science, Operations Research/Decision Theory, Artificial Intelligence, Artificial Intelligence, Mathematical and Computational Engineering, Industrial and Production Engineering