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Titlebook: Recent Advances in Evolutionary Multi-objective Optimization; Slim Bechikh,Rituparna Datta,Abhishek Gupta Book 2017 Springer International

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書目名稱Recent Advances in Evolutionary Multi-objective Optimization
編輯Slim Bechikh,Rituparna Datta,Abhishek Gupta
視頻videohttp://file.papertrans.cn/823/822744/822744.mp4
概述Provides both methodological treatments and real world insights.Serves as comprehensive reference for researchers, practitioners, and advanced-level students.Covers both the theory and practice of usi
叢書名稱Adaptation, Learning, and Optimization
圖書封面Titlebook: Recent Advances in Evolutionary Multi-objective Optimization;  Slim Bechikh,Rituparna Datta,Abhishek Gupta Book 2017 Springer International
描述This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domain
出版日期Book 2017
關鍵詞Computational Intelligence; Multi-Objective Optimization; Evolutionary Computation; Decision Making; Dyn
版次1
doihttps://doi.org/10.1007/978-3-319-42978-6
isbn_softcover978-3-319-82709-4
isbn_ebook978-3-319-42978-6Series ISSN 1867-4534 Series E-ISSN 1867-4542
issn_series 1867-4534
copyrightSpringer International Publishing Switzerland 2017
The information of publication is updating

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Evolutionary Bilevel Optimization: An Introduction and Recent Advances,ormous applications that are bilevel in nature; however, given the difficulties associated with solving this difficult class of problem, the area still lacks efficient solution methods capable of handling complex application problems. Most of the available solution methods can either be applied to h
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Dynamic Multi-objective Optimization Using Evolutionary Algorithms: A Survey, devoted to briefly survey EAs that were proposed in the literature to handle DMOPs. In addition, an overview of the most commonly used test functions, performance measures and statistical tests is presented. Actual challenges and future research directions are also discussed.
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1867-4534 ed-level students.Covers both the theory and practice of usiThis book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence,
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