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.
Product Identifiers
Publisher
Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg, Springer-Verlag Berlin and Heidelberg Gmbh & Co. K
ISBN-10
3540794379
ISBN-13
9783540794370
eBay Product ID (ePID)
95515539
Product Key Features
Format
Laminated Cover, Hardback
Language
English
Subject
Computing: Professional & Programming
Dimensions
Weight
586g
Height
234mm
Width
156mm
Additional Product Features
Place of Publication
Berlin
Spine
17mm
Edited by
Marc Sevaux, Carlos Cotta, Kenneth Sorensen
Series Part/Volume Number
V. 136
Series Title
Studies in Computational Intelligence
Content Note
41 Black & White Tables, Biography
Date of Publication
29/05/2008
Genre
Computing: Professional & Programming
Country of Publication
Germany
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