Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:A3L-A

Session:

Number:150

Searching Ability of PSO with Non-Convergent Particles

Takeshi Kamio,  Yuhei Itaki,  Hisato Fujisaka,  Kazuhisa Haeiwa,  

pp.150-153

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.150

PDF download (333.6KB)

Summary:
The number of particles affects the searching diversity of particle swarm optimization (PSO) directly. Therefore, if PSO is implemented on a useful searching conception, the increment of particles is the simplest way to improve the searching ability. However, if PSO does not have an enough control of the swarm behavior, the increment of particles cannot produce the searching diversity effectively.
In this paper, we propose a novel PSO which consists of normal particles and searching particles. The searching particles are non-convergent ones. Since they are used to control the searching direction and resolution, our PSO can produce the searching diversity effectively and maintain it. Finally, it has been confirmed by numerical simulations that our PSO has a high searching ability.

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