Adaptive and Multilevel Metaheuristics, Hardback Book

Adaptive and Multilevel Metaheuristics Hardback

Edited by Carlos Cotta, Marc Sevaux, Kenneth Sorensen

Part of the Studies in Computational Intelligence series

Description

One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance.

This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art.

Transferring a part of this customization effort to the algorithm itself -endowing it with smart mechanisms to self-adapt to the problem- has been a long pursued goal in the field of metaheuristics. These mechanisms can involve different aspects of the algorithm, such as for example, self-adjusting the parameters, self-adapting the functioning of internal components, evolving search strategies, etc. Recently, the idea of hyperheuristics, i.e., using a metaheuristic layer for adapting the search by selectively using different low-level heuristics, has also been gaining popularity.

This volume presents recent advances in the area of adaptativeness in metaheuristic optimization, including up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms, as well as cutting edge works on adaptive, self-adaptive and multilevel metaheuristics, with application to both combinatorial and continuous optimization.

Information

  • Format: Hardback
  • Pages: 275 pages, 41 Tables, black and white; XV, 275 p.
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Publication Date:
  • Category: Mathematics
  • ISBN: 9783540794370

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