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Item Details
Title: EVOLUTIONARY ALGORITHMS FOR SOLVING MULTI-OBJECTIVE PROBLEMS
By: Carlos A. Coello Coello, David A.van Veldhuizen, Gary B. Lamont
Format: Hardback

List price: £146.00


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ISBN 10: 0306467623
ISBN 13: 9780306467622
Publisher: KLUWER ACADEMIC PUBLISHERS GROUP
Series: Genetic Algorithms and Evolutionary Computation v. 5
Pages: 610
Description: Presents the various features of multi-objective evolutionary algorithms (MOEAs), with detailed customized forms suggested for a variety of applications. Also, MOEA discussion questions and possible research directions are presented at the end of each chapter.
Synopsis: The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and deterministic and stochastic techniques for solving these large dimensional optimization problems have risen out of operations research, decision science, engineering, computer science and other related disciplines. The explosion in computing power continues to arouse extraordinary interest in stochastic search algorithms that require high computational speed and very large memories. A generic stochastic approach is that of evolutionary algorithms (EA). Such algorithms have been demonstrated to be very powerful and generally applicable for solving different single objective problems. Their fundamental algorithmic structures can also be applied to solving many multi-objective problems. In this book, the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and unique fashion, with detailed customized forms suggested for a variety of applications.Also, extensive MOEA discussion questions and possible research directions are presented at the end of each chapter.
Illustrations: 1
Publication: Netherlands
Imprint: Kluwer Academic / Plenum Publishers
Returns: Non-returnable
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