Hybrid metaheuristics in combinatorial optimization: A survey

被引:528
作者
Blum, Christian [1 ]
Puchinger, Jakob [2 ]
Raidl, Guenther R. [3 ]
Roli, Andrea [4 ]
机构
[1] Univ Politecn Cataluna, ALBCOM Res Grp, Barcelona, Spain
[2] Austrian Inst Technol, Mobil Dept, Vienna, Austria
[3] Vienna Univ Technol, Inst Comp Graph & Algorithms, Vienna, Austria
[4] Univ Bologna, DEIS, I-40126 Bologna, Italy
基金
奥地利科学基金会;
关键词
Hybrid metaheuristics; Combinatorial optimization; Mathematical programming; Constraint programming; Local search; ANT COLONY OPTIMIZATION; VARIABLE NEIGHBORHOOD SEARCH; IMPROVED LOCAL SEARCH; GENETIC ALGORITHM; EVOLUTIONARY ALGORITHM; MEMETIC ALGORITHMS; DYNASEARCH ALGORITHM; PROGRAMMING APPROACH; BEAM SEARCH; TABU SEARCH;
D O I
10.1016/j.asoc.2011.02.032
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Research in metaheuristics for combinatorial optimization problems has lately experienced a noteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problem-oriented. Nowadays the focus is on solving the problem at hand in the best way possible, rather than promoting a certain metaheuristic. This has led to an enormously fruitful cross-fertilization of different areas of optimization. This cross-fertilization is documented by a multitude of powerful hybrid algorithms that were obtained by combining components from several different optimization techniques. Hereby, hybridization is not restricted to the combination of different metaheuristics but includes, for example, the combination of exact algorithms and metaheuristics. In this work we provide a survey of some of the most important lines of hybridization. The literature review is accompanied by the presentation of illustrative examples. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:4135 / 4151
页数:17
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