Overview
- Presents recent developments in hybrid metaheuristics
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 114)
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About this book
Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming.
The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.
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Keywords
Table of contents (9 chapters)
Editors and Affiliations
Bibliographic Information
Book Title: Hybrid Metaheuristics
Book Subtitle: An Emerging Approach to Optimization
Editors: Christian Blum, Maria José Blesa Aguilera, Andrea Roli, Michael Sampels
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-78295-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-78294-0Published: 11 April 2008
Softcover ISBN: 978-3-642-09697-6Published: 25 November 2010
eBook ISBN: 978-3-540-78295-7Published: 24 June 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 290
Topics: Mathematical and Computational Engineering, Artificial Intelligence