An improved artificial bee colony algorithm for solving parameter identification problems
by Xuemei You; Yinghong Ma; Zhiyuan Liu
International Journal of Computing Science and Mathematics (IJCSM), Vol. 8, No. 6, 2017

Abstract: Swarm intelligence algorithms (SIA) have shown excellent optimisation performance on many real world problems. Artificial bee colony (ABC) is one of the most popular SIA. However, ABC has some shortcomings. In this paper, we design an improved ABC, called IABC, which introduces a hybrid search strategy. To evaluate the optimisation ability of IABC, we run IABC on several famous benchmark functions. Experimental results show that IABC can achieve good solutions on the test functions. Finally, IABC is used to solve parameter identification problems. Two test instances are used for the simulation experiment. Results demonstrate that IABC can obtain a good matching to the target model.

Online publication date: Wed, 03-Jan-2018

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