Particle Swarm Optimization algorithm with multiple social learning structures Online publication date: Fri, 19-Jun-2009
by Pisut Pongchairerks, Voratas Kachitvichyanukul
International Journal of Operational Research (IJOR), Vol. 6, No. 2, 2009
Abstract: This paper proposes a variant of Particle Swarm Optimisation (PSO) algorithm which enhances the social learning structure of the standard PSO by incorporating multiple social best positions. The research in this paper analyses the effects of main parameters on the proposed algorithm's performance by using factorial experiment. To verify the research findings, this paper compares the proposed algorithm's performance to those of several well-known PSO algorithms. Eventually, the comparison results indicate that the proposed algorithm outperforms others.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com