Evolutionary Algorithms - The Role of Mutation and Recombination

Spears, William M.

ISBN 10: 3540669507 / ISBN 13: 9783540669500

Edité par Springer Berlin, 2000

A propos de cet article

mak. Bibl. / library TitelEvolutionary algorithms : the role of mutation and recombination ; with 23 tables / William M. Spears Person(en)Spears, William M. (Verfasser) VerlagBerlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London ; Milan ; Paris ; Singapore ; Tokyo : Springer Zeitliche EinordnungErscheinungsdatum: 2000 Umfang/FormatXIV, 222 S. : graph. Darst. ; 25 cm ISBN/Einband/Preis978-3-540-66950-0 Pp. : DM 69.00 3-540-66950-7 Pp. : DM 69.00 Sprache(n)Englisch (eng) BeziehungenNatural computing series AnmerkungenLiteraturverz. S. 213 - 217 SchlagwörterEvolutionärer Algorithmus Evolutionärer Algorithmus ; Rekombination Evolutionärer Algorithmus ; Mutation Evolutionärer Algorithmus ; Markov-Kette Sachgruppe(n)28 Informatik, Datenverarbeitung ; 27 Mathematik ; 32 Biologie In englischer Sprache. 222 pages. 230x150 mm.

N° de réf. du vendeur 241145

Détails bibliographiques

• Titre: Evolutionary Algorithms - The Role of Mutation and Recombination
• Éditeur: Springer Berlin
• Date de parution: 2000
• Langue: anglais
• ISBN à 10 chiffres: 3540669507
• ISBN à 13 chiffres: 9783540669500
• Reliure: Hardcover
• État de l'article: deutliche Gebrauchsspuren

A propos de ce titre

Synopsis

Despite decades of work in evolutionary algorithms, there remains a lot of uncertainty as to when it is beneficial or detrimental to use recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates prior theoretical work and introduces new theoretical techniques for studying evolutionary algorithms. An aggregation algorithm for Markov chains is introduced which is useful for studying not only evolutionary algorithms specifically, but also complex systems in general. Practical consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. A focus on discrete rather than real-valued representations allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.