DocumentCode :
2986961
Title :
An Improve PSO Based Hybrid Algorithms
Author :
Babaee, H. ; Khosravi, A.
Author_Institution :
Fac. of Electr. & Comput. Eng., Noushirvani Univ. of Technol., Babol, Iran
fYear :
2011
fDate :
12-14 Aug. 2011
Firstpage :
1
Lastpage :
5
Abstract :
This paper used Particle swarm optimization (PSO) algorithms and its hybrid algorithms such as PSOPC and UPSO for solving optimization problems. Particle swarm optimization with passive congregation (PSOPC) and the unified PSO algorithm is called UPSO use to improve the performance and convergence of standard PSO. Passive congregation is an important biological force preserving swarm integrity and presents a unified PSO to improve convergence. A hybrid PSO algorithm such as UPSO and PSOPC are tested with 6 benchmark functions and simulation result compared whit standard genetic algorithm and standard Particle swarm optimization algorithm, respectively. Experiment result indicates that the PSOPC and UPSO improve the search convergence and performance on the benchmark function significantly.
Keywords :
particle swarm optimisation; search problems; hybrid PSO algorithm; optimization problems; particle swarm optimization; passive congregation; search convergence; unified PSO algorithm; Birds; Convergence; Genetic algorithms; Mathematical model; Optimization; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management and Service Science (MASS), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6579-8
Type :
conf
DOI :
10.1109/ICMSS.2011.5999410
Filename :
5999410
Link To Document :
بازگشت