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Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms - Couverture rigide
Synopsis
The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. The book is intended for a wide readership.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.
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- ÉditeurSpringer-Verlag Berlin and Heidelberg GmbH & Co. K
- Date d'édition2009
- ISBN 10 3540959750
- ISBN 13 9783540959755
- ReliureRelié
- Langueanglais
- Nombre de pages271
- Coordonnées du fabricantnon disponible
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Evolutionary Multi-objective Optimization in Uncertain Environments
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Springer Berlin Heidelberg, 2009
ISBN 10 : 3540959750
ISBN 13 : 9783540959755
Neuf
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent results in Evolutionary Multi-objective Optimization in Uncertain EnvironmentsEvolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-. N° de réf. du vendeur 4902332
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Evolutionary Multi-objective Optimization in Uncertain Environments
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Berlin Springer Berlin Heidelberg Springer Mrz 2009, 2009
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ISBN 13 : 9783540959755
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. 'Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms' is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties. 271 pp. Englisch. N° de réf. du vendeur 9783540959755
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Evolutionary Multi-objective Optimization in Uncertain Environments : Issues and Algorithms
Edité par
Springer, Berlin, Springer Berlin Heidelberg, Springer, 2009
ISBN 10 : 3540959750
ISBN 13 : 9783540959755
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. 'Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms' is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties. N° de réf. du vendeur 9783540959755
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Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms (Studies in Computational Intelligence)
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Springer, 2009
ISBN 10 : 3540959750
ISBN 13 : 9783540959755
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