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An Improved Multi-strategy Ensemble Artificial Bee Colony Algorithm with Neighborhood Search

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Neural Information Processing (ICONIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9950))

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Abstract

Artificial bee colony (ABC) algorithm has been shown its good performance over many optimization problems. Recently, a multi-strategy ensemble ABC (MEABC) algorithm was proposed which employed three distinct solution search strategies. Although its such mechanism works well, it may run the risk of causing the problem of premature convergence when solving complex optimization problems. Hence, we present an improved version by integrating the neighborhood search operator of which object is to perturb the global best food source for better balancing the exploration and exploitation. Experiments are conducted on a set of 22 well-known benchmark functions, and the results show that both of the quality of final results and convergence speed can be improved.

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Acknowledgments

This work was supported by the Foundation of State Key Laboratory of Software Engineering (No. SKLSE2014-10-04), the National Natural Science Foundation of China (Nos. 61272212, 61462045, 61462043 and 61562042), the Science and Technology Foundation of Jiangxi Province (Nos. 20151BAB217007 and 20151BAB217014), and the Science and Technology Plan Projects of Jiangxi Provincial Education Department (No. GJJ150318).

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Authors and Affiliations

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

    Xinyu Zhou, Mingwen Wang, Jianyi Wan & Jiali Zuo

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  1. Xinyu Zhou
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  2. Mingwen Wang
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  3. Jianyi Wan
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  4. Jiali Zuo
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Corresponding author

Correspondence to Xinyu Zhou .

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Editors and Affiliations

  1. The University of Tokyo , Tokyo, Japan

    Akira Hirose

  2. Kobe University , Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology , Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University , Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences , Beijing, China

    Derong Liu

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Zhou, X., Wang, M., Wan, J., Zuo, J. (2016). An Improved Multi-strategy Ensemble Artificial Bee Colony Algorithm with Neighborhood Search. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9950. Springer, Cham. https://doi.org/10.1007/978-3-319-46681-1_58

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  • DOI: https://doi.org/10.1007/978-3-319-46681-1_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46680-4

  • Online ISBN: 978-3-319-46681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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