Expand-and-Reduce Algorithm of Particle Swarm Optimization

Authors:
Eiji Miyagawa;Toshimichi Saito
Affiliations:
Hosei University, Koganei, Tokyo, Japan 184-0002;Hosei University, Koganei, Tokyo, Japan 184-0002
Venue:
Neural Information Processing
Year:
2007

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Abstract

This paper presents an optimization algorithm: particle swarm optimization with expand-and-reduce ability. When particles are trapped into a local optimal solution, a new particle is added and the trapped particle(s) can escape from the trap. The deletion of the particle is also used in order to suppress excessive network grows. The algorithm efficiency is verified through basic numerical experiments.