Recent Advances in Evolutionary Computation for Combinatorial Optimization

Jano van Hemert

ISBN 10: 3540708065 / ISBN 13: 9783540708063

Edité par Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 2008, 2008

A propos de cet article

Neuware -Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 356 pp. Englisch.

N° de réf. du vendeur 9783540708063

Détails bibliographiques

• Titre: Recent Advances in Evolutionary Computation for Combinatorial Optimization
• Éditeur: Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 2008
• Date de parution: 2008
• Langue: anglais
• ISBN à 10 chiffres: 3540708065
• ISBN à 13 chiffres: 9783540708063
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 241 L x 160 H x 24 P (en millimètres) 241 millimètres de largeur par 160 millimètres de hauteur par 24 millimètres de profondeur
• Poids: 699 grammes

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Synopsis

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.

The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective.