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Titlebook: Contemporary Evolution Strategies; Thomas Bäck,Christophe Foussette,Peter Krause Book 2013 Springer-Verlag Berlin Heidelberg 2013 CMA-ES.C

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书目名称Contemporary Evolution Strategies
编辑Thomas Bäck,Christophe Foussette,Peter Krause
视频video
概述Modern, comprehensive treatment of the key approaches.Authors‘ software available for download.Valuable for industrial and academic researchers and practitioners.Includes supplementary material:
丛书名称Natural Computing Series
图书封面Titlebook: Contemporary Evolution Strategies;  Thomas Bäck,Christophe Foussette,Peter Krause Book 2013 Springer-Verlag Berlin Heidelberg 2013 CMA-ES.C
描述.Evolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for strategy parameter adaptation. Most importantly, the covariance matrix adaptation strategy (CMA-ES) and its successors are the key representatives of this group of contemporary evolution strategies. .This book provides an overview of the key algorithm developments between 1990 and 2012, including brief descriptions of the algorithms, a unified pseudocode representation of each algorithm, and program code which is available for download. In addition, a taxonomy of these algorithms is provided to clarify similarities and differences as well as historical relationships between the various instances of evolution strategies. Moreover, due to the authors’ focus on industrial applications of nonlinear optimization, all algorithms are empirically compared on the so-called BBOB (Black-Box Optimization Benchmarking) test function suite, and ranked according to their performance. In contrast to classical academic compari
出版日期Book 2013
关键词CMA-ES; Constraint handling; Evolution strategy (ES); Evolutionary algorithm (EA); Evolutionary computin
版次1
doihttps://doi.org/10.1007/978-3-642-40137-4
isbn_softcover978-3-662-51408-5
isbn_ebook978-3-642-40137-4Series ISSN 1619-7127 Series E-ISSN 2627-6461
issn_series 1619-7127
copyrightSpringer-Verlag Berlin Heidelberg 2013
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Introduction,some algorithmic variants have been incorporated into standardized off-the-shelf software toolboxes. Between 1990—when the first author of this book entered into the field which was known under the term “genetic algorithms” only—and today, the field has seen tremendous development and has earned enormous scientific recognition.
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Evolution Strategies,t with, the definition of an optimization task as used throughout this book is given in Sect. 2.1.1. Following [58], Sect. 2.1.2 presents a discussion of evolution strategy metaheuristics as a special case of evolutionary algorithms.
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Summary,ts to empirically analyze the efficiency of contemporary ES were conducted. Usually such experiments are performed on standardized test functions with many function evaluations using an analysis approach which is not suited to the optimization scenarios considered in this book.
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