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Evolutionary Optimization (International Series in Operations Research & Management Science)

by Ruhul Sarker (Editor), Masoud Mohammadian (Editor), Xin Yao (Editor)

ISBN-10: 9780792376545
ISBN-10: 0-7923-7654-4
ISBN-13: 9780792376545
ISBN-13: 978-0-7923-7654-5
Hardcover
2002-01-01
Springer


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Editorials


Product Description

The use of evolutionary computation techniques has grown considerably over the past several years. Over this time, the use and applications of these techniques have been further enhanced resulting in a set of computational intelligence (also known as modern heuristics) tools that are particularly adept for solving complex optimization problems. Moreover, they are characteristically more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. Hence, evolutionary computation techniques have dealt with complex optimization problems better than traditional optimization techniques although they can be applied to easy and simple problems where conventional techniques work well. Clearly there is a need for a volume that both reviews state-of-the-art evolutionary computation techniques, and surveys the most recent developments in their use for solving complex OR/MS problems. This volume on Evolutionary Optimization seeks to fill this need.

Evolutionary Optimization is a volume of invited papers written by leading researchers in the field. All papers were peer reviewed by at least two recognized reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.


Reviews


EAs for Optimization
Its a great book which covers cross disciplinary research outcomes. The book is designed like a text book although the chapters were written by different leading researchers in the world. It covers from basic optimizations concepts to complex applications of EAs to theoretical and practical optimization problems. The book is suitable for new researcher or post-grade students in Operations Research / Management Science, Optimization, Industrial Engineering and Computer Science.


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