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Titlebook: Recent Developments in Metaheuristics; Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui Book 2018 Springer International Publishing AG 2018 M

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發(fā)表于 2025-3-21 19:58:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Recent Developments in Metaheuristics
編輯Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui
視頻videohttp://file.papertrans.cn/824/823197/823197.mp4
概述Examines recent research and current developments in metaheuristics.Highlights the design and application of metaheuristics in different domains of optimization.Editors are leading experts in the fiel
叢書名稱Operations Research/Computer Science Interfaces Series
圖書封面Titlebook: Recent Developments in Metaheuristics;  Lionel Amodeo,El-Ghazali Talbi,Farouk Yalaoui Book 2018 Springer International Publishing AG 2018 M
描述This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics
出版日期Book 2018
關(guān)鍵詞Metaheuristics; Combinatorial Optimization; Continuous Optimization; Multi-objective Optimization; Opera
版次1
doihttps://doi.org/10.1007/978-3-319-58253-5
isbn_softcover978-3-319-86360-3
isbn_ebook978-3-319-58253-5Series ISSN 1387-666X Series E-ISSN 2698-5489
issn_series 1387-666X
copyrightSpringer International Publishing AG 2018
The information of publication is updating

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Possibilistic Framework for Multi-Objective Optimization Under Uncertainty,nce, few works on multi-objective optimization under uncertainty exist today. In our study, we address combinatorial multi-objective problem under uncertainty using the possibilistic framework. To this end, we firstly propose new Pareto relations for ranking the generated uncertain solutions in both
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Combining Neighborhoods into Local Search Strategies,ecify when neighborhoods should be explored, and introduce other aspects of the search procedures such as stop criteria, solution management, and various metaheuristics. Our approach introduces these higher-level concepts natively in local search frameworks in contrast with the current practice whic
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All-Terrain Tabu Search Approaches for Production Management Problems,metaheuristic works on a single solution and tries to improve it iteratively.Tabu search is one of the most famous local search, where at each iteration, a neighbor solution is generated from the current solution by performing a specific modification (called a move) on the latter. The goal of this c
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POSL: A Parallel-Oriented Metaheuristic-Based Solver Language,now available to a broad public through hardware like the Xeon Phi or GPU cards. This architecture strategy has been commonly adopted by processor manufacturers, allowing them to stick with Moore’s law. However, this new architecture implies new ways to design and implement algorithms to exploit its
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Theory Driven Design of Efficient Genetic Algorithms for a Classical Graph Problem, shortest path problemis selected to demonstrate how level-based analysis, a general purpose analytical tool, can be used as a design guide. We show that level-based analysis can also ease the experimental burden of finding appropriate parameter settings. Apart from providing an example of theory-dr
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On the Impact of Representation and Algorithm Selection for Optimisation in Process Design: Motivatm. However, although some methods may be more widely applicable than others, it is impossible a priori to know which method will work best. This may be due to the particular mathematical properties of the mathematical model, i.e. the formulation. It may also be due to the representation of the varia
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發(fā)表于 2025-3-23 08:01:43 | 只看該作者
Manufacturing Cell Formation Problem Using Hybrid Cuckoo Search Algorithm,pplications. The cell formation problemis considered the first and the foremost issue faced in the designing of cellular manufacturing systems that attempts to minimize the inter-cell movement of the products while maximize the machines utilization. This paper presents an adapted optimization algori
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