Title: Modified artificial bee colony based on random neighbourhood

Authors: Kefeng Li; Na Jin; Jun Tang; Yiqing Cao

Addresses: Department of Architecture, Hunan Urban Construction College, Xiangtan, 411101, China ' Department of Architecture, Hunan Urban Construction College, Xiangtan, 411101, China ' Department of Construction Equipment Engineering, Hunan Urban Construction College, Xiangtan, 411101, China ' Department of Library, Changsha University, Changsha, 410003, China

Abstract: Neighbourhood search is meaningful for the optimisation capability of artificial bee colony (ABC). In this paper, a modified ABC based on random neighbourhood structure (RNS) is presented. The new ABC is called modified version based on RNS (MABCRNS), which designs two search equations based on RNS. For the onlooker bees, a new selection strategy based on RNS is employed for choosing good solutions. To validate the performance of MABCRNS, nine famous benchmark problems are tested. Simulation experiments reveal the new strategies work well in the proposed MABCRNS.

Keywords: ABC; artificial bee colony; RNS; random neighbourhood structure; neighbourhood search; probability selection; global optimisation.

DOI: 10.1504/IJCSM.2024.142730

International Journal of Computing Science and Mathematics, 2024 Vol.20 No.3, pp.188 - 196

Received: 11 Jun 2024
Accepted: 26 Jul 2024
Published online: 19 Nov 2024 *

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