Exploitation of Linkage Learning in Evolutionary Algorithms - Couverture rigide

Couverture rigide

ISBN 10 : 3642128335 ISBN 13 : 9783642128332

Editeur : Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2010

Synopsis

The exploitation of linkage learning is enhancing the performance of evolutionary algorithms. This monograph examines recent progress in linkage learning, with a series of focused technical chapters that cover developments and trends in the field.

A propos du livre

Présentation de l'éditeur

One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Détails de l'édition

• Éditeur: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
• Date d'édition: 2010
• Langue: anglais
• ISBN 10: 3642128335
• ISBN 13: 9783642128332
• Reliure: Relié
• Nombre de pages: 256
• Éditeur: Chen Ying-ping
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne