Title: Improved slime mould algorithm by perfecting bionic-based mechanisms

Authors: Tianyu Yu; Jiawen Pan; Qian Qian; Miao Song; Jibin Yin; Yong Feng; Yunfa Fu; Yingna Li

Addresses: Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China ' College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China ' Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China ' School of Information and Engineering, Shanghai Maritime University, Shanghai 201306, China ' Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China ' Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China

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.

Keywords: slime mould algorithm; meta-heuristic algorithm; bionic modelling.

DOI: 10.1504/IJBIC.2023.133504

International Journal of Bio-Inspired Computation, 2023 Vol.22 No.1, pp.1 - 15

Received: 14 Dec 2021
Accepted: 26 Dec 2022
Published online: 18 Sep 2023 *

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