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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 284.
Da: Majestic Books, Hounslow, Regno Unito
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 135,27
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Aggiungi al carrelloCondizione: New. pp. 284.
Lingua: Inglese
Editore: Springer, Berlin, Springer, 2009
ISBN 10: 3540959750 ISBN 13: 9783540959755
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 111,53
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Aggiungi al carrelloBuch. Condizione: 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.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 186,00
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Da: Mispah books, Redhill, SURRE, Regno Unito
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Berlin Springer Berlin Heidelberg Springer Mrz 2009, 2009
ISBN 10: 3540959750 ISBN 13: 9783540959755
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 106,99
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Aggiungi al carrelloBuch. Condizione: 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.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2009
ISBN 10: 3540959750 ISBN 13: 9783540959755
Da: moluna, Greven, Germania
EUR 93,00
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Aggiungi al carrelloGebunden. Condizione: 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-.