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Titlebook: Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications; Serdar Carbas,Abdurrahim Toktas,Deniz Ustun Book 2021

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書目名稱Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications
編輯Serdar Carbas,Abdurrahim Toktas,Deniz Ustun
視頻videohttp://file.papertrans.cn/663/662076/662076.mp4
概述Presents concise overviews of various nature-inspired metaheuristic algorithms.Provides solutions to specific engineering optimization problems with single and multi-objectives.Serves as a reference f
叢書名稱Springer Tracts in Nature-Inspired Computing
圖書封面Titlebook: Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications;  Serdar Carbas,Abdurrahim Toktas,Deniz Ustun Book 2021
描述This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications..
出版日期Book 2021
關鍵詞Nature-Inspired Optimization Algorithms; Metaheuristics; Design Optimization; Discrete And Combinatori
版次1
doihttps://doi.org/10.1007/978-981-33-6773-9
isbn_softcover978-981-33-6775-3
isbn_ebook978-981-33-6773-9Series ISSN 2524-552X Series E-ISSN 2524-5538
issn_series 2524-552X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Book 2021on problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficient
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