Constrained solution of CEC 2017 with monarch butterfly optimisation
by Hui Hu; Zhaoquan Cai; Song Hu; Yingxue Cai; Jia Chen; Sibo Huang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 16, No. 2, 2019

Abstract: Recently, inspired by the behaviour of monarch butterfly in North America, Wang et al. proposed a new kind of swarm intelligence algorithm, called Monarch Butterfly Optimisation (MBO). Since it was proposed, it has been widely studied and applied in various engineering fields. In this paper, we apply MBO algorithm to solve CEC 2017 competition on constrained real-parameter optimisation. Also, the performance of MBO on 21 constrained CEC 2017 real-parameter optimisation problems is compared with five other state-of-the-art evolutionary algorithms. The experimental results indicate that MBO algorithm performs much better than other five evolutionary algorithms on most cases. It is strongly proven that MBO is a very promising algorithm for solving constrained engineering problems.

Online publication date: Fri, 12-Apr-2019

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