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Artificial Bee Colony Algorithm with an Adaptive Search Manner

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Neural Computing for Advanced Applications (NCAA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1449))

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Abstract

Artificial bee colony (ABC) can effectively solve some complex optimization problems. However, its convergence speed is slow and its exploitation capacity is insufficient at the last search stage. In order to solve these problems, this paper proposes a modified ABC with an adaptive search manner (called ASMABC). There are two important search manners: exploration and exploitation. A suitable search manner is beneficial for the search. Then, an evaluating indicator is designed to relate the current search status. An explorative search strategy and another exploitative search strategy are selected to build a strategy pool. According to the evaluating indicator, an adaptive method is used to determine which kind of search manner is suitable for the current search. To verify the performance of ASMABC, 22 complex problems are tested. Experiment result shows that ASMABC achieves competitive performance when contrasted with four different ABC variants.

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Authors and Affiliations

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

    Tingyu Ye, Tao Zeng, Luqi Zhang, Minyang Xu, Hui Wang & Min Hu

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  1. Tingyu Ye
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  2. Tao Zeng
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  3. Luqi Zhang
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  4. Minyang Xu
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  5. Hui Wang
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  6. Min Hu
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Corresponding author

Correspondence to Hui Wang .

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Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Nanfang College of Sun Yat-sen University, Guangzhou, China

    Zhi Yang

  3. Hefei University of Technology, Hefei, China

    Zhao Zhang

  4. Chongqing University, Chongqing, China

    Zhou Wu

  5. South China Normal University, Guangzhou, China

    Tianyong Hao

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Ye, T., Zeng, T., Zhang, L., Xu, M., Wang, H., Hu, M. (2021). Artificial Bee Colony Algorithm with an Adaptive Search Manner. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_35

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  • DOI: https://doi.org/10.1007/978-981-16-5188-5_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5187-8

  • Online ISBN: 978-981-16-5188-5

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