Articoli correlati a Parameter Setting in Evolutionary Algorithms: 54

Parameter Setting in Evolutionary Algorithms: 54 - Rilegato

 
9783540694311: Parameter Setting in Evolutionary Algorithms: 54
Rilegato
ISBN 10: 3540694315 ISBN 13: 9783540694311
Casa editrice: Springer Nature, 2007

Sinossi

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.

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Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Nature
Data di pubblicazione
2007
Lingua
Inglese
ISBN 10 
3540694315
ISBN 13 
9783540694311
Rilegatura
Copertina rigida
Numero di pagine
317
Redattore
Lobo Fernando G., Lima Claudio F., Michalewicz Zbigniew
Contatto del produttore
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

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