Improved slime mould algorithm by perfecting bionic-based mechanisms Online publication date: Mon, 18-Sep-2023
by Tianyu Yu; Jiawen Pan; Qian Qian; Miao Song; Jibin Yin; Yong Feng; Yunfa Fu; Yingna Li
International Journal of Bio-Inspired Computation (IJBIC), Vol. 22, No. 1, 2023
Abstract: Slime mould algorithm (SMA) is a new meta-heuristic algorithm which imitates the biological mechanism of natural creatures. It has good initial performance, but it also has some disadvantages. More importantly, the bionic modelling of SMA is not complete, and many biological mechanisms of slime moulds are ignored. This paper proposes an improved slime mould algorithm by perfecting bionic mechanism (IBSMA). Specifically, three mechanisms are added. Among them, the 'polar growth' mechanism is used to improve the global optimisation ability, the 'memory' mechanism is used to enhance the ability of the algorithm to jump out of the local optimum, and the 'amoeba' mechanism is used to expand the search space and improve the exploration capability of the algorithm. Qualitative and effectiveness analyses are conducted, and the proposed algorithm is compared with nine excellent algorithms. The results show that IBSMA has the best performance, which is also verified by non-parametric statistical methods.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook