A survey on optimization metaheuristics

被引：1120

作者：

Boussaid, Ilhern ^{[1
]}

Lepagnot, Julien ^{[2
]}

Siarry, Patrick ^{[2
]}

机构：

[1] Univ Sci & Technol Houari Boumed, Dept Elect Engn & Comp Sci, Algiers 16111, Algeria

[2] Univ Paris Est Creteil, LiSSi, F-94010 Creteil, France

来源：

INFORMATION SCIENCES | 2013年 / 237卷

关键词：

Population based metaheuristic; Single solution based metaheuristic; Intensification; Diversification; PARTICLE SWARM OPTIMIZATION; ANT COLONY OPTIMIZATION; GUIDED LOCAL SEARCH; VARIABLE NEIGHBORHOOD SEARCH; CMA EVOLUTION STRATEGY; DIFFERENTIAL EVOLUTION; CULTURAL ALGORITHMS; GENETIC ALGORITHMS; SELF-ADAPTATION; DISTRIBUTED OPTIMIZATION;

D O I：

10.1016/j.ins.2013.02.041

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Metaheuristics are widely recognized as efficient approaches for many hard optimization problems. This paper provides a survey of some of the main metaheuristics. It outlines the components and concepts that are used in various metaheuristics in order to analyze their similarities and differences. The classification adopted in this paper differentiates between single solution based metaheuristics and population based metaheuristics. The literature survey is accompanied by the presentation of references for further details, including applications. Recent trends are also briefly discussed. (c) 2013 Elsevier Inc. All rights reserved.

引用

页码：82 / 117

页数：36

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