An enhanced gravitational search algorithm for global optimisation
by Zhaolu Guo; Haixia Huang; Huogen Yang; Shenwen Wang; Hui Wang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 9, No. 3, 2015

Abstract: Numerous problems in science and engineering can be converted into optimisation problems. Gravitational Search Algorithm (GSA) is a newly developed optimisation algorithm inspired by Newton's law of gravity and law of motion. However, the traditional GSA tends to suffer from trapping in local minima when solving complex problems. This paper proposes an enhanced gravitational search algorithm (GOGSA), which utilises the generalised opposition-based learning to enhance the search ability. Experiments are conducted on 13 classical test functions. The experimental results and analysis demonstrate that GOGSA can obtain better performance on the majority of the test functions.

Online publication date: Thu, 19-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 Wireless and Mobile Computing (IJWMC):
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