Condizione: New.
Editore: Nova Science Publishers Inc, 2006
ISBN 10: 1594543909 ISBN 13: 9781594543906
Lingua: Inglese
Da: PBShop.store US, Wood Dale, IL, U.S.A.
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Editore: Nova Science Publishers Inc, 2006
ISBN 10: 1594543909 ISBN 13: 9781594543906
Lingua: Inglese
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 191,15
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Aggiungi al carrelloCondizione: New. 2005. Hardcover. . . . . .
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Editore: Nova Science Publishers Inc, 2006
ISBN 10: 1594543909 ISBN 13: 9781594543906
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 181,17
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Aggiungi al carrelloGebunden. Condizione: New. Aims to provide a representation of the evolutionary multi-objective optimisation research area and related trends. This book reports many innovative designs yielded by the application of such optimisation methods. It is divided into two main parts: evoluti.
Condizione: New. 2005. Hardcover. . . . . . Books ship from the US and Ireland.
Editore: Nova Science Publishers Inc Mär 2006, 2006
ISBN 10: 1594543909 ISBN 13: 9781594543906
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 233,76
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Real-world engineering problems often require concurrent optimisation of several design objectives, which are conflicting in most of the cases. Such an optimisation is generally called multi-objective or multi-criterion optimisation. The area of research that applies evolutionary methodologies to multi-objective optimisation is of special and growing interest. It brings a solution to many yet-opened real-world problems and questions. Generally, multi-objective engineering problems have no single optimal design, but several solutions of equal efficiency allowing different trade-offs. The decision maker's preferences are normally used to select the most adequate design. Such preferences may be dictated before or after the optimisation takes place. They may also be introduced interactively at different levels of the optimisation process. Multi-objective optimisation methods can be subdivided into classical and evolutionary. The classical methods usually aim at a single solution while the evolutionary methods target a whole set of so-called Pareto-optimal solutions. The aim of this book is to provide a representation of the state-of-the-art of the evolutionary multi-objective optimisation research area and related new trends. Furthermore, it reports many innovative designs yielded by the application of such optimisation methods. The contents of the book are divided into two main parts: evolutionary multi-objective optimisation and evolutionary multi-objective designs.