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Titlebook: Evolutionary Algorithms for Solving Multi-Objective Problems; Carlos A. Coello Coello,Gary B. Lamont,David A. Va Textbook 2007Latest editi

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書目名稱Evolutionary Algorithms for Solving Multi-Objective Problems
編輯Carlos A. Coello Coello,Gary B. Lamont,David A. Va
視頻videohttp://file.papertrans.cn/318/317814/317814.mp4
概述Designed for courses on Evolutionary Multi-objective Optimization and Evolutionary Algorithms.2nd Edition is completely updated and presents the latest research.Provides a complete set of teaching tut
叢書名稱Genetic and Evolutionary Computation
圖書封面Titlebook: Evolutionary Algorithms for Solving Multi-Objective Problems;  Carlos A. Coello Coello,Gary B. Lamont,David A. Va Textbook 2007Latest editi
描述.Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. ..This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations..
出版日期Textbook 2007Latest edition
關(guān)鍵詞Algorithms; Analysis; algorithm; classification; computer; computer science; evolutionary algorithm; heuris
版次2
doihttps://doi.org/10.1007/978-0-387-36797-2
isbn_softcover978-1-4899-9460-8
isbn_ebook978-0-387-36797-2Series ISSN 1932-0167 Series E-ISSN 1932-0175
issn_series 1932-0167
copyrightSpringer-Verlag US 2007
The information of publication is updating

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MOEA Testing and Analysis, and ensuring their reproducibility. Specifically, they suggest that a well-designed experiment follows the following steps: 1. Define experimental goals; 2. Choose measures of performance - metrics; 3. Design and execute the experiment; 4. Analyze data and draw conclusions; 5. Report experimental r
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Applications,the focus of the work. For example, a paper that is related to scheduling and naval engineering but is more focused on the second subject, is classified under “environmental, naval and hydraulic engineering”. This avoids overlapping to a certain extent, but can be confusing for some people. Therefor
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