A modified particle swarm optimization algorithm

被引：0
|
作者：
Jiang Yan [1 ]
Hu Tiesong [1 ]
Huang Chongchao [1 ]
Wu Xianing [1 ]
机构：
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
来源：
2006 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PTS 1 AND 2, PROCEEDINGS | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A shuffled complex evolution of particle swarm optimization algorithm called SCE-PSO is introduced in this paper. In SCE-PSO, a Population of points sampled randomly from the feasible space is partitioned into several complexes, each of which is permitted to evolve independently based on particle swarm optimization (PSO). At periodic stages in the evolution, the entire population is shuffled and points are reassigned to complexes to ensure information sharing. In the simulation part, numerical experiences and case study are performed, and the performance of the proposed algorithm is compared to PSO to demonstrate its efficiency.
引用
收藏
页码：421 / 424
页数：4
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