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Evolutionary Algorithms for Solving Multi-objective Problems (Genetic Algorithms and Evolutionary Computation)

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Evolutionary Algorithms for Solving Multi-objective Problems (Genetic Algorithms and Evolutionary Computation) (Hardcover)

by Carlos A. Coello Coello (Author), David A. Van Veldhuizen (Author), Gary B. Lamont (Author)

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This item: Evolutionary Algorithms for Solving Multi-objective Problems (Genetic Algorithms and Evolutionary Computation) by Carlos A. Coello Coello

Multi-objective Optimization Using Evolutionary Algorithms (Wiley Paperback) by Kalyanmoy Deb

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This item: Evolutionary Algorithms for Solving Multi-objective Problems (Genetic Algorithms and Evolutionary Computation) by Carlos A. Coello Coello
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Multi-objective Optimization Using Evolutionary Algorithms (Wiley Paperback) by Kalyanmoy Deb
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Product details

Hardcover: 610 pages
Publisher: Springer; illustrated edition edition (30 Jun 2002)
Language English
ISBN-10: 0306467623
ISBN-13: 978-0306467622
Product Dimensions: 24.1 x 16.4 x 4.1 cm
Average Customer Review: No customer reviews yet. Be the first.
Amazon.co.uk Sales Rank: 3,081,828 in Books (See Bestsellers in Books)

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Product Description

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.

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