Unconstrained optimisation through bat algorithm
by Shruti Goel; Nishant Goel; Divya Gupta
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 2, No. 4, 2014

Abstract: Swarm-based metaheuristic algorithms have bridged the gap from ideal situation to reality. They have been successful in removing the limitations of conventional methods by providing optimal and sub-optimal solutions to those optimisation problems which were earlier considered next to impossible. Their characteristics such as self-organisation and decentralisation have led to these advancements in literature. In this paper, the performance of one such nature inspired algorithm namely the bat algorithm has been tabulated on the basis of precision and convergence speed. The conclusions drawn from the performance and observations are also described later.

Online publication date: Sat, 07-Feb-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 Intelligent Engineering Informatics (IJIEI):
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