Memetic particle swarm optimization

被引：0
|
作者：
Y. G. Petalas
K. E. Parsopoulos
M. N. Vrahatis
机构：
[1] University of Patras,Computational Intelligence Laboratory (CI Lab), Department of Mathematics, University of Patras Artificial Intelligence Research Center (UPAIRC)
来源：
Annals of Operations Research | 2007年 / 156卷
关键词：
Global optimization; Particle swarm optimization; Memetic algorithms; Local search;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are compared to that of the global and local variants of Particle Swarm Optimization, justifying the superiority of the memetic approach.
引用
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页码：99 / 127
页数：28
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