Title: Artificial bee colony with multiple search strategies and a new updating mechanism

Authors: Xin Li; Kai Li; Tao Zeng; Tingyu Ye; Luqi Zhang; Hui Wang

Addresses: School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China

Abstract: The imbalance of exploration and exploitation is a weakness in artificial bee colony (ABC) algorithm. To overcome this deficiency, this paper presents an improved ABC (IABC) by employing multiple search strategies and a novel updating method. Firstly, a concept of marginal group is introduced to construct an exploration search strategy. Then, an exploitation search strategy is designed utilising some excellent solutions. Thirdly, the probabilistic selection strategy is modified on this basis of some elite solutions. In the experiments, 22 benchmark problems were utilised to prove the effectiveness of IABC. Test results indicate that IABC achieves stronger optimisation capabilities than the other five ABCs.

Keywords: ABC; artificial bee colony; marginal group; multiple search strategies; selection mechanism.

DOI: 10.1504/IJCSM.2023.133532

International Journal of Computing Science and Mathematics, 2023 Vol.18 No.1, pp.44 - 53

Received: 26 Nov 2021
Accepted: 12 Feb 2022
Published online: 19 Sep 2023 *

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