Parameter setting in evolutionary algorithms

One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operato...

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Detaylı Bibliyografya
Yazar: Lobo, Fernando G.
Diğer Yazarlar: Lima, Cláudio F. (Yayın yönetmeni), Michalewicz, Zbigniew, 1952-...., chercheur en informatique (Yayın yönetmeni)
Materyal Türü: Livre numérique
Dil:Anglais
Baskı/Yayın Bilgisi: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Edisyon:1st ed. 2007.
Seri Bilgileri:Studies in Computational Intelligence 54
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Not: Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Parameter setting in evolutionary algorithms, with 100 figures and 24 tables, Fernando G. Lobo, Cláudio F. Lima, Zbigniew Michalewicz, (eds.), Berlin, Springer, 2007, 1 vol. (XII-317 p.), Studies in computational intelligence, 978-3-540-69431-1
• Parameter Setting in Evolutionary Algorithms, Texte imprimé, 9783540834625
• Parameter Setting in Evolutionary Algorithms, Texte imprimé, 9783642088926
Diğer Bilgiler
Özet:One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods
Diğer Bilgileri:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783540694328
ISSN:1860-9503
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