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Titlebook: Hybrid Metaheuristics; An Emerging Approach Christian Blum,Maria José Blesa Aguilera,Michael S Book 2008 Springer-Verlag Berlin Heidelberg

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发表于 2025-3-21 16:34:55 | 显示全部楼层 |阅读模式
书目名称Hybrid Metaheuristics
副标题An Emerging Approach
编辑Christian Blum,Maria José Blesa Aguilera,Michael S
视频video
概述Presents recent developments in hybrid metaheuristics.Includes supplementary material:
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Hybrid Metaheuristics; An Emerging Approach Christian Blum,Maria José Blesa Aguilera,Michael S Book 2008 Springer-Verlag Berlin Heidelberg
描述.Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming...The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments..
出版日期Book 2008
关键词algorithm; algorithms; behavior; combinatorial optimization; computational intelligence; constraint progr
版次1
doihttps://doi.org/10.1007/978-3-540-78295-7
isbn_softcover978-3-642-09697-6
isbn_ebook978-3-540-78295-7Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2008
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发表于 2025-3-21 21:56:14 | 显示全部楼层
Hybrid Metaheuristics for Multi-objective Combinatorial Optimization,act and heuristic approaches. In this chapter we give an overview over approximation methods in multi-objective combinatorial optimization. We briefly summarize “classical” metaheuristics and focus on recent approaches, where metaheuristics are hybridized and/or combined with exact methods.
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Hybridizations of Metaheuristics With Branch & Bound Derivates, branch & bound, respectively branch & bound derivatives such as beam search. The quality of the resulting hybrid techniques is demonstrated by means of the application to classical string problems: the longest common subsequence problem and the shortest common supersequence problem.
发表于 2025-3-22 16:41:27 | 显示全部楼层
Hybrids of Constructive Metaheuristics and Constraint Programming: A Case Study with ACO, for each type. The central distinction is between tight coupling in which both components collaborate in an interleaved fashion and loose coupling where both components run in parallel, exchanging only (partial) solutions and bounds.
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Hybrid Metaheuristics for Packing Problems,and mathematical programming techniques of linear, nonlinear and/or dynamic programming. Basic ideas of these algorithms are explained on a unified basis, together with some computational results. It appears to indicate that mathematical programming is a vital tool for enhancing metaheuristic algorithms.
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