Editors:
- Unique in its treatment of the new linkage technology in Adaptive Memory Programming (AMP), which allows researchers to link major heuristic strategies together and the linked combination provides a wider and more problem-solving power
Part of the book series: Operations Research/Computer Science Interfaces Series (ORCS, volume 30)
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Table of contents (20 chapters)
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Front Matter
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Advances for New Model and Solution Approaches
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Advances for Solving Classical Problems
About this book
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
Editors and Affiliations
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Oklahoma State University, USA
Ramesh Sharda
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Universität Hamburg, Germany
Stefan Voß
Bibliographic Information
Book Title: Metaheuristic Optimization via Memory and Evolution
Book Subtitle: Tabu Search and Scatter Search
Editors: Ramesh Sharda, Stefan Voß, César Rego, Bahram Alidaee
Series Title: Operations Research/Computer Science Interfaces Series
DOI: https://doi.org/10.1007/b102147
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2005
Hardcover ISBN: 978-1-4020-8134-7Published: 11 January 2005
Softcover ISBN: 978-1-4419-5483-1Published: 08 December 2010
eBook ISBN: 978-0-387-23667-4Published: 30 March 2006
Series ISSN: 1387-666X
Series E-ISSN: 2698-5489
Edition Number: 1
Number of Pages: XIV, 466
Number of Illustrations: 69 b/w illustrations
Topics: Operations Research, Management Science, Optimization, Operations Research/Decision Theory, Mathematical and Computational Engineering