Paperback. The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comrephensive coverage of this growing area of research.Carefully introduces each algorithm with examples and in-depth discussion.Includes many applications to real-world problems, including engineering design and scheduling.Includes discussion of advanced topics and future research.Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms Provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches. This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing. Comprehensive coverage of this growing area of research. Carefully introduces each algorithm with examples and in-depth discussion. Includes many applications to real-world problems, including engineering design and scheduling. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Multi-Objective Optimization Using Evolutionary Algorithms (Paperback)
Editor: John Wiley & Sons Inc, New York
Fecha de publicaci�n: 2008
Idioma: Ingl�s
ISBN 10: 0470743611
ISBN 13: 9780470743614
Encuadernaci�n: Paperback
Edici�n: 1� Edici�n
Estado: new

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Sinopsis

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.

Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run.

Comrephensive coverage of this growing area of research.
Carefully introduces each algorithm with examples and in-depth discussion.
Includes many applications to real-world problems, including engineering design and scheduling.
Includes discussion of advanced topics and future research.
Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms

Provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches.

This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.

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Kalyanmoy Deb is an Indian computer scientist. Since 2013, Deb has held the Herman E. & Ruth J. Koenig Endowed Chair in the Department of Electrical and Computing Engineering at Michigan State University, which was established in 2001.

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