Title: Cuckoo search with dual-subpopulation and information-sharing strategy

Authors: Jun Xi; Li-Ming Zheng

Addresses: Department of Electronic Engineering, School of Information Science and Technology, Jinan University, Guangzhou 510632, China ' Department of Electronic Engineering, School of Information Science and Technology, Jinan University, Guangzhou 510632, China

Abstract: Cuckoo search (CS) algorithm is simple and powerful in dealing with the global optimisation problem. However, how to strike a good balance between exploration and exploitation in CS is still an open question. The paper proposes a modified CS with dual-subpopulation and information-sharing strategy (DSIS_CS). In DSIS_CS, the population is divided into two subpopulations which are assigned different update tasks. Then, random solutions are selected from the dissimilar subpopulations in order to avoid the results from easily falling into the local optima. In addition, the DSIS strategy can be incorporated into other state-of-the-art CS variants to improve their optimisation performance. Extensive experiments on 28 functions chosen from CEC 2013 have been carried out. The results suggest that the DSIS strategy helps both the CS and its variants to achieve a better trade-off between exploration and exploitation.

Keywords: cuckoo search algorithm; swarm intelligence; global optimisation; dual-subpopulation strategy.

DOI: 10.1504/IJCSM.2021.120681

International Journal of Computing Science and Mathematics, 2021 Vol.14 No.4, pp.315 - 327

Received: 22 Mar 2019
Accepted: 14 May 2019
Published online: 03 Feb 2022 *

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