Self-Adaptive Heuristics for Evolutionary Computation - Couverture souple

Kramer, Oliver

Couverture souple

ISBN 10 : 3642088783 ISBN 13 : 9783642088780

Editeur : Springer, 2010

Synopsis

Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to be exceptionally successful. But nevertheless self-adaptation has not achieved the attention it deserves.

This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.

A propos du livre

Présentation de l'éditeur

This book introduces various types of self-adaptive parameters for evolutionary computation. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2010
• Langue: anglais
• ISBN 10: 3642088783
• ISBN 13: 9783642088780
• Reliure: Broché
• Nombre de pages: 196
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne