DocumentCode :
1639961
Title :
Scalability of the vector-based Particle Swarm Optimizer
Author :
Schoeman, I.L. ; Engelbrecht, A.P.
Author_Institution :
Dept. of Comput. Sci., Univ. of Pretoria, Pretoria
fYear :
2009
Firstpage :
1995
Lastpage :
2001
Abstract :
This paper presents an investigation into the scalability of the vector-based PSO, a niching algorithm using particle swarm optimization. The vector-based PSO locates and maintains niches by using vector operations to determine niche boundaries. The technique builds upon existing knowledge of the particle swarm in such a way that the swarm can be organized into subswarms without prior knowledge of the number of niches in the search space and the corresponding niche radii, thus reducing the number of user-specified parameters. In a designated search space a linear increase in the number of dimensions often results in an exponential or near exponential increase in the number of optima. Empirical results are reported where the vector-based PSO is tested on three multimodal functions in one to four dimensions using a range of swarm sizes. Optimal swarm sizes are derived where all or most of the optima should be located.
Keywords :
particle swarm optimisation; search problems; vectors; niching algorithm; scalability; search space; vector-based particle swarm optimizer; Africa; Algorithm design and analysis; Computer science; Design optimization; Monitoring; Optimization methods; Particle swarm optimization; Robustness; Scalability; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
Type :
conf
DOI :
10.1109/CEC.2009.4983185
Filename :
4983185
Link To Document :
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