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Gaussian bare-bones artificial bee colony algorithm

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Abstract

As a relatively new global optimization technique, artificial bee colony (ABC) algorithm becomes popular in recent years for its simplicity and effectiveness. However, there is still an inefficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this drawback, a Gaussian bare-bones ABC is proposed, where a new search equation is designed based on utilizing the global best solution. Furthermore, we employ the generalized opposition-based learning strategy to generate new food sources for scout bees, which is beneficial to discover more useful information for guiding search. A comprehensive set of experiments is conducted on 23 benchmark functions and a real-world optimization problem to verify the effectiveness of the proposed approach. Some well-known ABC variants and state-of-the-art evolutionary algorithms are used for comparison. The experimental results show that the proposed approach offers higher solution quality and faster convergence speed.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61305150, 61364025, and 61462045), the Science and Technology Plan Projects of Jiangxi Provincial Education Department (Nos. GJJ13729 and GJJ14747 ), the Science and Technology Foundation of Jiangxi Province (No. 20142BAB217020), and the Humanity and Social Science Foundation of Ministry of Education of China (No. 13YJCZH174).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, 330022, China

    Xinyu Zhou

  2. State Key Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan, 430072, China

    Zhijian Wu

  3. School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China

    Hui Wang

  4. Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology (OUIT), 2000 Simcoe Street North, Oshawa, ON, L1H 7K4, Canada

    Shahryar Rahnamayan

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  1. Xinyu Zhou
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Correspondence to Xinyu Zhou.

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Communicated by V. Loia.

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Zhou, X., Wu, Z., Wang, H. et al. Gaussian bare-bones artificial bee colony algorithm. Soft Comput 20, 907–924 (2016). https://doi.org/10.1007/s00500-014-1549-5

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