On simultaneous perturbation particle swarm optimization

Authors:
Yutaka Maeda;Naoto Matsushita;Seiji Miyoshi;Hiroomi Hikawa
Affiliations:
Department of Electrical and Electronic Engineering, Faculty of Engineering Science, Kansai University, Suita, Japan;Kansai University, Suita, Japan;Department of Electrical and Electronic Engineering, Faculty of Engineering Science, Kansai University, Suita, Japan;Department of Electrical and Electronic Engineering, Faculty of Engineering Science, Kansai University, Suita, Japan
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

In this paper, we describes the simultaneous perturbation particle swarm optimization which is a combination of the particle swarm optimization and the simultaneous perturbation optimization method. The method has global search capability of the particle swarm optimization and local search one of gradient method by the simultaneous perturbation. Some variations of the method are described. Comparison between these methods and the ordinary particle swarm optimization are shown through five test functions and learning problem of neural networks.