An enhanced harmony search integrated with adaptive mutation strategy
by Ying Deng; Yiwen Zhong; Lijin Wang
International Journal of Computing Science and Mathematics (IJCSM), Vol. 16, No. 2, 2022

Abstract: Aiming at making improvements on solutions to function optimisation problems, an enhanced harmony search, called EHS, is proposed by hybridising differential mutation strategies. EHS employs differential mutation strategies after a solution generated by harmony search, then the solution is integrated into the differential mutation strategies as a target or current vector. Moreover, four differential mutation operators, including target-to-rand/1, target-to-rand/2, target-to-best/1 and target-to-best/2 are invoked adaptively in a random way. Extensive experiments on CEC2014 benchmark functions demonstrate EHS is effective and efficient with the combination of harmony search and the differential mutation strategies.

Online publication date: Mon, 19-Dec-2022

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