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Titlebook: Design of Heuristic Algorithms for Hard Optimization; With Python Codes fo éric D. Taillard Textbook‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applica

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書目名稱Design of Heuristic Algorithms for Hard Optimization
副標題With Python Codes fo
編輯éric D. Taillard
視頻videohttp://file.papertrans.cn/269/268718/268718.mp4
概述This book is open access, which means that you have free and unlimited access.Offers step-by-step procedures for the design of heuristic algorithms.Contains numerous short illustrative codes for the t
叢書名稱Graduate Texts in Operations Research
圖書封面Titlebook: Design of Heuristic Algorithms for Hard Optimization; With Python Codes fo éric D. Taillard Textbook‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applica
描述.This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed. This problem is ideal for introducing readers to the subject because it is very intuitive and its solutions can be graphically represented. The book features a wealth of illustrations that allow the concepts to be understood at a glance.. . The book approaches the main metaheuristics from a new angle, deconstructing them into a few key concepts presented in separate chapters: construction, improvement, decomposition, randomization and learning methods. Each metaheuristic can then be presented in simplified form as a combination of these concepts. This approach avoids giving the impression that metaheuristics is a non-formal discipline, a kind of cloud sculpture. Moreover, it provides concrete applications of the travelling salesman problem, whichillustrate in just a few lines of code how to design a new heuristic and remove all ambiguities left by a general framework. Two chapters reviewing the basics of combinatorial optimization and complexity theo
出版日期Textbook‘‘‘‘‘‘‘‘ 2023
關(guān)鍵詞Algorithms; Heuristics; Travelling Salesman; Local Search; Metaheuristics; Combinatorial Optimization; Art
版次1
doihttps://doi.org/10.1007/978-3-031-13714-3
isbn_softcover978-3-031-13716-7
isbn_ebook978-3-031-13714-3Series ISSN 2662-6012 Series E-ISSN 2662-6020
issn_series 2662-6012
copyrightThe Editor(s) (if applicable) and The Author(s) 2023
The information of publication is updating

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Ting Sun,Yun Li,Lina Xu,Kevin F. KellyThis chapter is devoted to random and memory-free methods that repeatedly construct solutions or modify them. Among the most popular techniques, there are simulated annealing, threshold accepting, great deluge and demon algorithms, noising methods, late acceptance hill climbing, variable neighborhood search, and GRASP.
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