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 :
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