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
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