Research on Cellular Artificial Bee Colony Algorithm and its Computational Experiments

Abstract:

It is the research hotspot for evolutionary algorithms to solve the contradiction between exploration and exploitation. Cellular artificial bee colony (CABC) algorithm is proposed by combining cellular automata with artificial bee colony algorithm from the perspective of the neighborhood in this paper. Each bee in the population structure defined in CABC has a fixed position and can only interact with bees in its neighborhood. The overlap between neighborhoods of different bees may make a bee an employed bee in one neighborhood and an onlooker bee in another neighborhood and vice versa, which increases the diversity of the population. The neighborhood and evolutionary rule help to control the selection pressure effectively, and the improved search mechanism in artificial bee colony algorithm is proposed to enhance the local search ability. The experimental results tested on four benchmark functions show that CABC can further balance the relationship between exploration and exploitation when compared with three ABC-based algorithms.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 3168-3172
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.3168
• Online since: January 2013
• Authors: Ren Bin Xiao, Ying Cong Wang
• Keywords: Artificial Bee Colony, Benchmark Function, Cellular Automata (CA), Computational Experiment

References

[1] D. Karaboga: Technical Report-TR06 (Erciyes University, Turkey, OCTOBER, 2005).

[2] D. Karaboga, B. Basturk: Journal of Global Optimization, Vol. 39 (2007), p.459.

[3] D. Karaboga, B. Akay: Applied Mathematics and Computation, Vol. 214 (2009), p.108.

[4] B. Akay, D. Karaboga : Information Sciences, Vol. 192 (2012), p.120.

[5] G.P. Zhu, S. Kwong: Applied Mathematics and Computation, Vol. 217 (2010), p.3166.

[6] W.F. Gao, S.Y. Liu: Information Processing Letters, Vol. 111 (2011), p.871.

[7] W.F. Gao, S.Y. Liu: Computers & Operations Research, Vol. 39 (2012), p.687.

[8] E. Alba,B. Dorronsoro: Cellular genetic algorithms, Springer Science + Business Media, (2008).

[9] G. Zhu, L. Ma: Control and Decision (In Chinese), Vol. 22 (2007), p.1317.

[10] Y. Liu, L. Ma: Journal of System & Management (In Chinese), Vol. 19 (2010), p.351.

[11] Y. Liu, L. Ma: Journal of Management Sciences in China (In Chinese), Vol. 14 (2011), p.86.

[12] Y. Shi, H.C. Liu, L. Gao, and G.H. Zhang: Information Sciences, Vol. 181 (2011), p.4460.