| 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video | http://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 |  |
| 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 |
| 關鍵詞 | algorithms; computer-aided design (CAD); evolution; evolutionary algorithm; evolutionary computation; mul |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-540-95976-2 |
| isbn_softcover | 978-3-642-10113-7 |
| isbn_ebook | 978-3-540-95976-2Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer-Verlag Berlin Heidelberg 2009 |
|Archiver|手機版|小黑屋|
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