9783642101137 - Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms de Goh, Chi-Keong; Tan, Kay Chen (11 résultats)

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Taschenbuch. Etat : Neu. Evolutionary Multi-objective Optimization in Uncertain Environments | Issues and Algorithms | Chi-Keong Goh (u. a.) | Taschenbuch | Studies in Computational Intelligence | xi | Englisch | 2010 | Springer | EAN 9783642101137 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. 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.

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Taschenbuch. 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. 284 pp. Englisch.

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-.

Etat : New. Print on Demand pp. 284 113 Illus.

Etat : New. PRINT ON DEMAND pp. 284.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 284 pp. Englisch.