DocumentCode
2501022
Title
An improved two particles PSO algorithm
Author
Li, Ming ; Yang, Cheng ; Yang, Cheng-wu
Author_Institution
Coll. of Commun., Southwest Forestry Coll., Kunming
fYear
2008
fDate
25-27 June 2008
Firstpage
8743
Lastpage
8748
Abstract
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.
Keywords
convergence; nonlinear programming; particle swarm optimisation; probability; search problems; stochastic programming; algorithm convergence; global optimization solution; global search ability; nonlinear test functions; particle swarm optimization; probability; stochastic searches; Automation; Civil engineering; Educational institutions; Forestry; Intelligent control; Machinery; Particle swarm optimization; Power engineering; Stochastic processes; Testing; PSO algorithm; global convergence; two particles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4594306
Filename
4594306
Link To Document