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Titlebook: Evolutionary Multi-objective Optimization in Uncertain Environments; Issues and Algorithm Chi-Keong Goh,Kay Chen Tan Book 2009 Springer-Ver

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發(fā)表于 2025-3-21 17:15:08 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Evolutionary Multi-objective Optimization in Uncertain Environments
副標題Issues and Algorithm
編輯Chi-Keong Goh,Kay Chen Tan
視頻videohttp://file.papertrans.cn/318/317990/317990.mp4
概述Presents recent results in Evolutionary Multi-objective Optimization in Uncertain Environments.Includes supplementary material:
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Evolutionary Multi-objective Optimization in Uncertain Environments; Issues and Algorithm Chi-Keong Goh,Kay Chen Tan Book 2009 Springer-Ver
描述.Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. ...The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimi
出版日期Book 2009
關(guān)鍵詞algorithms; computer-aided design (CAD); evolution; evolutionary algorithm; evolutionary computation; mul
版次1
doihttps://doi.org/10.1007/978-3-540-95976-2
isbn_softcover978-3-642-10113-7
isbn_ebook978-3-540-95976-2Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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Evolutionary Multi-objective Optimization in Uncertain EnvironmentsIssues and Algorithm
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Robust Evolutionary Multi-objective Optimizationt suite with features of noise-induced solution space, fitness landscape and decision space variation. In addition, the vehicle routing problem with stochastic demand (VRPSD) is presented a practical example of robust combinatorial multi-objective optimization problems.
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https://doi.org/10.1007/978-3-658-35330-8t suite with features of noise-induced solution space, fitness landscape and decision space variation. In addition, the vehicle routing problem with stochastic demand (VRPSD) is presented a practical example of robust combinatorial multi-objective optimization problems.
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