Modified constriction particle swarm optimization algorithm

被引：2
|
作者：
Zhang, Zhe [1 ,2 ]
Jia, Limin [2 ,3 ]
Qin, Yong [2 ,3 ]
机构：
[1] Beijing Jiaotong Univ, Traff & Transportat Sch, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
[3] Beijing Jiaotong Univ, Beijing Res Ctr Urban Traff Informat Sensing & Se, Beijing 100044, Peoples R China
来源：
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2015年 / 26卷 / 05期
基金：
中国国家自然科学基金;
关键词：
particle swarm optimization; random speed operator; convergence; global optima; CONVERGENCE ANALYSIS; MULTIAGENT SYSTEMS; CONSENSUS; OPTIMA;
D O I：
10.1109/JSEE.2015.00120
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To deal with the demerits of constriction particle swarm optimization (CPSO), such as relapsing into local optima, slow convergence velocity, a modified CPSO algorithm is proposed by improving the velocity update formula of CPSO. The random velocity operator from local optima to global optima is added into the velocity update formula of CPSO to accelerate the convergence speed of the particles to the global optima and reduce the likelihood of being trapped into local optima. Finally the convergence of the algorithm is verified by calculation examples.
引用
收藏
页码：1107 / 1113
页数：7
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