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A multi-objective artificial bee colony algorithm based on division of the searching space

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Abstract

This paper presents a new multi-objective artificial bee colony algorithm called dMOABC by dividing the whole searching space S into two independent parts S 1 and S 2. In this algorithm, two ”basic” colonies are assigned to search potential solutions in regions S 1 and S 2, while the so-called ”synthetic” colony explores in S. This multi-colony model could enable the good diversity of the population, and three colonies share information in a special way. A fixed-size external archive is used to store the non-dominated solutions found so far. The diversity over the archived solutions is controlled by utilizing a self-adaptive grid. For basic colonies, neighbor information is used to generate new food sources. For the synthetic colony, besides neighbor information, the global best food source gbest selected from the archive, is also adopted to guide the flying trajectory of both employed and onlooker bees. The scout bees are used to get rid of food sources with poor qualities. The proposed algorithm is evaluated on a set of unconstrained multi-objective test problems taken from CEC09, and is compared with 11 other state-of-the-art multi-objective algorithms by applying Friedman test in terms of four indicators: HV, SPREAD, EPSILON and IGD. It is shown by the test results that our algorithm significantly surpasses its competitors.

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Notes

  1. url= http://jmetal.sourceforge.net/

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Acknowledgments

The authors thank the anonymous reviewers for providing valuable comments to improve this paper, and add special thanks to J.J. Durillo and A.J. Nebro for their open source jMetal software package.

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Authors and Affiliations

  1. School of Mathematics and Information Sciences & Key Laboratory of Mathematics and Interdisciplinary Sciences of Guangdong Higher Education Institutes, Guangzhou University, Guangzhou, 510006, China

    Yu-Bin Zhong

  2. Department of Advanced Mathematics, Guangdong Baiyun University, Guangzhou, 510450, People’s Republic of China

    Yi Xiang

  3. Department of Applied Mathematics, Guangdong University of Technology, Guangzhou, 510090, People’s Republic of China

    Hai-Lin Liu

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  1. Yu-Bin Zhong
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  2. Yi Xiang
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  3. Hai-Lin Liu
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Correspondence to Yi Xiang or Hai-Lin Liu.

Additional information

This paper is supported by National Natural Science Foundation of China under Grant 61350003 and the Project of Department of Education of Guangdong Province(No.20131130543031) and by the major Research Project of Guangdong Baiyun University (No. BYKY201317).

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Zhong, YB., Xiang, Y. & Liu, HL. A multi-objective artificial bee colony algorithm based on division of the searching space. Appl Intell 41, 987–1011 (2014). https://doi.org/10.1007/s10489-014-0555-8

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