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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2016: Intelligent Information and Database Systems pp 636–643Cite as

A Segmented Artificial Bee Colony Algorithm Based on Synchronous Learning Factors

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

Abstract

In this paper, we propose a segmented ABC algorithm based on synchronous learning factors (SABC). For the problem of inferior local search ability and low convergence precision in the artificial bee colony (ABC) algorithm, we use the method of synchronous change learning factors for local search. Then under the guidance of the segmented thought, it updates the quality honey greedily. It improves the efficiency of nectar source updating, enhances the local search ability of artificial bee colony. The six standard test functions are chosen to do the simulation experiments. Compared with the other three experiments, the results show that SABC has a significant improvement in the convergence speed and searching optimal value.

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Author information

Authors and Affiliations

  1. Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, Ministry of Education, Dalian, 116622, China

    Yu Li, Dongsheng Zhou & Qiang Zhang

  2. School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, China

    Jianxia Zhang

Authors
  1. Yu Li
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  2. Jianxia Zhang
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  3. Dongsheng Zhou
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  4. Qiang Zhang
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Corresponding authors

Correspondence to Dongsheng Zhou or Qiang Zhang .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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© 2016 Springer-Verlag Berlin Heidelberg

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Li, Y., Zhang, J., Zhou, D., Zhang, Q. (2016). A Segmented Artificial Bee Colony Algorithm Based on Synchronous Learning Factors. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_61

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  • DOI: https://doi.org/10.1007/978-3-662-49381-6_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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