Adaptive and Multilevel Metaheuristics (Paperback, Softcover reprint of hardcover 1st ed. 2008)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Studies in Computational Intelligence, 136
Release date:	October 2010
First published:	2008
Editors:	Carlos Cotta • Marc Sevaux • Kenneth Soerensen
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Paperback
Pages:	275
Edition:	Softcover reprint of hardcover 1st ed. 2008
ISBN-13:	978-3-642-09833-8
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-642-09833-9
Barcode:	9783642098338

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