A Hybrid Particle Swarm Optimization Algorithm Based on Space Transformation Search and a Modified Velocity Model
Year: 2012
International Journal of Numerical Analysis and Modeling, Vol. 9 (2012), Iss. 2 : pp. 371–377
Abstract
Particle Swarm Optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO often easily falls into local optima because the particles would quickly get closer to the best particle. Under these circumstances, the best particle could hardly be improved. This paper proposes a new hybrid PSO (HPSO) to solve this problem by combining space transformation search (STS) with a new modified velocity model. Experimental studies on 8 benchmark functions demonstrate that the HPSO holds good performance in solving both unimodal and multimodal functions optimization problems.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2012-IJNAM-634
International Journal of Numerical Analysis and Modeling, Vol. 9 (2012), Iss. 2 : pp. 371–377
Published online: 2012-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 7
Keywords: Space Transformation Search (STS) evolutionary algorithm Particle Swarm Optimization (PSO) optimization.