Particle swarm optimisation for dynamic optimisation problems: a review

被引：54
|
作者：
Jordehi, Ahmad Rezaee [1 ]
机构：
[1] Univ Putra Malaysia, Dept Elect Engn, Serdang 43400, Malaysia
来源：
NEURAL COMPUTING & APPLICATIONS | 2014年 / 25卷 / 7-8期
关键词：
Particle swarm optimisation; Optimisation; Dynamic optimisation problem; ALGORITHM; OPTIMA; STRATEGY; SYSTEM; MODEL; PSO;
D O I：
10.1007/s00521-014-1661-6
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Some real-world optimisation problems are dynamic; that is, their objective function and/or constraints vary over time. Solving such problems is very challenging. Particle swarm optimisation (PSO) is a well-known and efficient optimisation algorithm. In this paper, the PSO variants, devised for dynamic optimisation problems, are reviewed. This is the first comprehensive review that is conducted on PSO variants in dynamic environments. The author believes that this paper can be useful for researchers who intend to solve dynamic optimisation problems.
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页码：1507 / 1516
页数：10
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