Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.
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Etat : New. The use of evolutionary computation techniques has grown considerably. The use and applications of these techniques have been further enhanced resulting in a set of computational intelligence tools that are adept for solving complex optimization problems. This book covers the foundation as well as the practical side of evolutionary optimization. Editor(s): Sarker, Ruhul Amin; Mohammadian, M.; Yao, X. Series: International Series in Operations Research & Management Science. Num Pages: 418 pages, biography. BIC Classification: KJT; PBU. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 23. Weight in Grams: 1730. . 2002. Hardback. . . . . N° de réf. du vendeur V9780792376545
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Gebunden. Etat : New. Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS pr. N° de réf. du vendeur 458442161
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