DocumentCode :
2206698
Title :
A novel particle swarm optimization algorithm with stochastic focusing search for real-parameter optimization
Author :
Weibo, Wang ; Quanyuan, Feng ; Yongkang, Zheng
Author_Institution :
Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu, China
fYear :
2008
fDate :
19-21 Nov. 2008
Firstpage :
583
Lastpage :
587
Abstract :
Basic particle swarm optimization (PSO) algorithms are susceptible to being trapped into local optimum and premature convergence. A novel stochastic focusing search (SFS) based PSO algorithm with adaptively dynamic neighborhoods topology and subpopulation strategy is proposed. SFS is based on simulating the act of human randomized searching behaviors by using the adaptively dynamic neighborhoods topology. With subpopulation strategy, SFS can improve the global searching ability, keeping the diversity and escaping local extremum. The algorithm¿s performance is studied by using a challenging set of typically complex functions with comparison of differential evolution (DE) and three modified PSO algorithms. The simulation results show that SFS is competitive to solve most parts of the benchmark problems and will become a promising candidate of search algorithms especially when the existing algorithms have difficulties in solving some problems.
Keywords :
particle swarm optimisation; search problems; topology; adaptively dynamic neighborhoods topology; particle swarm optimization; real-parameter optimization; stochastic focusing search; subpopulation strategy; Centralized control; Control systems; Heuristic algorithms; Humans; Information science; Insects; Particle swarm optimization; Search methods; Stochastic processes; Topology; particle swarm optimization; real-parameter optimization; stochastic focusing search; swarm intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-2423-8
Electronic_ISBN :
978-1-4244-2424-5
Type :
conf
DOI :
10.1109/ICCS.2008.4737251
Filename :
4737251
Link To Document :
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