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Synopsis
In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.
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- PublisherSpringer
- Publication date2010
- ISBN 10 3642064108
- ISBN 13 9783642064104
- BindingPaperback
- LanguageEnglish
- Number of pages342
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Representations for Genetic and Evolutionary Algorithms
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Representations for Genetic and Evolutionary Algorithms
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Representations for Genetic and Evolutionary Algorithms
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Springer Berlin Heidelberg Okt 2010, 2010
ISBN 10: 3642064108
ISBN 13: 9783642064104
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations. 344 pp. Englisch. Seller Inventory # 9783642064104
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Representations for Genetic and Evolutionary Algorithms
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ISBN 10: 3642064108
ISBN 13: 9783642064104
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A theory of representations is not taken as given, but is developed and applied to real-world problems of commercial importance Considers basic concepts of representations, such as redundancy, scaling and locality Completely overhauled 2nd edition . Seller Inventory # 5045521
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Representations for Genetic and Evolutionary Algorithms
Published by
Springer Berlin Heidelberg, 2010
ISBN 10: 3642064108
ISBN 13: 9783642064104
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations. Seller Inventory # 9783642064104
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Representations for Genetic and Evolutionary Algorithms
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Representations for Genetic and Evolutionary Algorithms
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