DocumentCode :
2221093
Title :
PSO2: Particle swarm optimization with PSO-based local search
Author :
Khairy, Mohamed ; Fayek, Magda B. ; Hemayed, Elsayed E.
Author_Institution :
Comput. Eng. Dept., Cairo Univ., Cairo, Egypt
fYear :
2011
fDate :
5-8 June 2011
Firstpage :
1826
Lastpage :
1832
Abstract :
Several attempts have been made to enhance PSO performance by combining it with a local search method. Following the same track, we present in this paper local search in PSO performed by smaller independent swarms of PSO producing PSO2. Different modifications are made to help basic PSO2 enhance performance. PSO2-RS and PSO2-SA are 2 modified versions of PSO2 that targeted to increase the swarm diversity. Increasing the local search swarms sizes as the search progresses is another modification made to basic PSO2 in order to change the algorithm behavior to be more exploitive. The final algorithm is examined against 4 functions of the CEC-2005 benchmark suite and results are reported.
Keywords :
particle swarm optimisation; search problems; PSO-based local search method; PSO2-RS; PSO2-SA; particle swarm optimization; swarm diversity; Benchmark testing; Convergence; Heuristic algorithms; Particle swarm optimization; Search methods; Simulated annealing; Topology; Hybridization; Local Search; Optimization; PSO2; Particle Swarm Optimization; Swarm Intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
ISSN :
Pending
Print_ISBN :
978-1-4244-7834-7
Type :
conf
DOI :
10.1109/CEC.2011.5949837
Filename :
5949837
Link To Document :
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