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
fDate :
6/24/1905 12:00:00 AM
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;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004460
