An Improved Two Particles PSO Algorithm

被引：1

作者：

Li, Ming ^{[1
]}

Yang, Cheng ^{[1
]}

Yang, Cheng-wu ^{[2
]}

机构：

[1] Southwest Forestry Coll, Coll Commun Machinery & Civil Engn, Kunming 650224, Peoples R China

[2] Nanjing Univ Sci & Technol, Coll Power Engn, Nanjing 210094, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

PSO algorithm; global convergence; two particles;

D O I：

10.1109/WCICA.2008.4594306

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 order to reduce the size and improve the convergence of PSO (Particle Swarm Optimization) algorithm, an improved PSO algorithm, called TPSO (Two Particles PSO) algorithm, is presented in this paper. The swarm is only composed of two particles in TPSO algorithm. The algorithm is guaranteed to converge to the global optimization solution with probability one. Its global search ability is enhanced through re-initialize the particles at every moment. Executing several stochastic searches continuously around the best position of the swarm can enhance its local search ability. Simulation results show that TPSO algorithm can converge to the global optimization solution of three standard nonlinear test functions rapidly.

引用

页码：8743 / +

页数：2

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