Swarm-based approximate dynamic optimization process for discrete particle swarm optimization system
by Qi Kang, Lei Wang, Qidi Wu
International Journal of Bio-Inspired Computation (IJBIC), Vol. 1, No. 1/2, 2009

Abstract: This paper presents a convergence analysis of particle swarm optimisation system by treating it as a discrete-time linear time-variant system firstly. And then, based on the results of system convergence conditions, dynamic optimal control of a deterministic PSO system for parameters optimisation is studied by using dynamic programming; and an approximate dynamic programming algorithm – swarm-based approximate dynamic programming (swarm-ADP) is proposed in this paper. Finally, numerical simulations proved the validated of this presented dynamic optimisation method.

Online publication date: Mon, 26-Jan-2009

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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 Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your 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