Comparison between Differential Evolution and Particle Swarm Optimization Algorithms

被引:0
|
作者
Zhang, Dan [1 ]
Wei, Bin [1 ]
机构
[1] Univ Ontario, Inst Technol, Dept Automot Mech & Mfg Engn, Oshawa, ON L1H 7K4, Canada
关键词
optimization algorithm; differential evolution (DE); particle swarm optimization (PSO);
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, the performance of differential evolution ( DE) and particle swarm optimization (PSO) algorithms are compared and evaluated. The comparison is performed on eight benchmark functions f1-f8. New findings have been discovered for the PSO algorithm and the comparison results in this report show that DE generally is better than PSO in term of solution accuracy and robustness in almost all the problems. Generally, from the numerical results and graphic illustrations, we can demonstrate that DE is more efficient and robust compare to PSO, although PSO gives good results in some cases.
引用
收藏
页码:239 / 244
页数:6
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