Title: Artificial bee colony algorithm with improved special centre

Authors: Hui Sun; Kun Wang; Jia Zhao; Xiang Yu

Addresses: School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang, 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang, 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang, 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang, 330099, China

Abstract: Artificial bee colony (ABC) algorithm is a powerful stochastic evolutionary algorithm, which is widely used to solve complex optimisation problems. However, ABC is good at exploration but poor at exploitation because of its search strategy. For overcoming the shortcomings of original ABC algorithm, such as slow convergence and low solution accuracy, we propose a new ABC algorithm - artificial bee colony algorithm with improved special centre (ISC-ABC). Firstly, an improved special centre is used to determine the current gbest position, and lead the colony convergence. Secondly, Employed bees incorporate the information of gbest solution into the search strategy. By this way, the new candidate solutions are always around with gbest. Finally, compare result on 12 classic functions. The results testify that ISC-ABC performs significantly better than original ABC and several recently proposed similar algorithm.

Keywords: artificial bee colony; ABC; special centre; average fitness; search mechanism; metaheuristics; swarm intelligence.

DOI: 10.1504/IJCSM.2016.081698

International Journal of Computing Science and Mathematics, 2016 Vol.7 No.6, pp.548 - 553

Received: 16 Jun 2016
Accepted: 08 Aug 2016
Published online: 20 Jan 2017 *

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