Hybrid Metaheuristics : Powerful Tools for Optimization / by Christian Blum, Günther R. Raidl
(Artificial Intelligence: Foundations, Theory, and Algorithms. ISSN:2365306X)
| データ種別 | 電子ブック |
|---|---|
| 版 | 1st ed. 2016. |
| 出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
| 出版年 | 2016 |
| 大きさ | XVI, 157 p. 20 illus., 9 illus. in color : online resource |
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| 一般注記 | Introduction -- Incomplete Solution Representations and Decoders -- Hybridization Based on Problem Instance Reduction -- Hybridization Based on Large Neighborhood Search -- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics -- Hybridization Based on Complete Solution Archives -- Further Hybrids and Conclusions. This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains HTTP:URL=https://doi.org/10.1007/978-3-319-30883-8 |
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| 著者標目 | *Blum, Christian author Raidl, Günther R author SpringerLink (Online service) |
| 件 名 | LCSH:Artificial intelligence LCSH:Computer science LCSH:Computational intelligence LCSH:Operations research LCSH:Mathematical optimization FREE:Artificial Intelligence FREE:Theory of Computation FREE:Computational Intelligence FREE:Operations Research and Decision Theory FREE:Optimization |
| 分 類 | LCC:Q334-342 LCC:TA347.A78 DC23:006.3 |
| 巻冊次 | ebook ; ISBN:9783319308838 
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| ISBN | 9783319308838 |
| URL | https://doi.org/10.1007/978-3-319-30883-8 |
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※2021年9月12日以降