The variable HSS iteration based on the bacterial foraging optimisation algorithm
by Guo-Yan Meng; Qing-Shan Zhao; Yulan Hu
International Journal of Computing Science and Mathematics (IJCSM), Vol. 6, No. 5, 2015

Abstract: In the Hermitian and skew-Hermitian splitting (HSS) iteration method, the determination of the optimal parameter is a tough task when solving a large sparse non-Hermitian positive definite linear systems. In this paper, we present the variable HSS iteration with the non-fixed positive constant. For obtaining the approximate optimal parameters of this method, we solve the minimising the optimisation model based on the bacterial foraging optimisation (BFO) algorithm. Numerical experiments have shown that the new strategy is feasible and effective than the HSS iteration method.

Online publication date: Tue, 10-Nov-2015

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 Computing Science and Mathematics (IJCSM):
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