DocumentCode
1635438
Title
Particle swarm optimisation with spatial particle extension
Author
Krink, Thiemo ; Vesterstrom, J.S. ; Riget, Jacques
Author_Institution
Dept. of Comput. Sci., Aarhus Univ., Denmark
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1474
Lastpage
1479
Abstract
In this paper, we introduce spatial extension to particles in the PSO model in order to overcome premature convergence in iterative optimisation. The standard PSO and the new model (SEPSO) are compared w.r.t. performance on well-studied benchmark problems. We show that the SEPSO indeed managed to keep diversity in the search space and yielded superior results
Keywords
genetic algorithms; PSO model iterative optimisation; benchmark problems; particle swarm optimisation; spatial extension; spatial particle extension; Birds; Computer science; Convergence; Cultural differences; Educational institutions; Evolutionary computation; Marine animals; Particle swarm optimization; Performance loss; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7282-4
Type
conf
DOI
10.1109/CEC.2002.1004460
Filename
1004460
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