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An Effective Artificial Bee Colony for Distributed Lot-Streaming Flowshop Scheduling Problem

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Intelligent Computing Methodologies (ICIC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10956))

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Abstract

This paper proposes an effective discrete artificial bee colony (DABC) algorithm for solving the distributed lot-streaming flowshop scheduling problem (DLFSP) with the objective of minimizing makespan. We design a multi-list based representation to represent candidate solutions, where each list is corresponding to a factory. We present a multi-list based swap and insertion operators to generate neighboring solutions. We redesign the employ bee phase, onlooker bee phase, and scout bee phase according to the problem-specific knowledge, representation and information collected in the evolution process. The parameters for the proposed DABC algorithm are calibrated by means of a design of experiments and analysis of variance. A comprehensive computational campaign based on 810 randomly generated instances demonstrates the effectiveness of the proposed DABC algorithm for solving the DLFSP with the makespan criterion.

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Acknowledgements

This research is partially supported by the National Science Foundation of China 51575212 and 61174187, and Shanghai Key Laboratory of Power station Automation Technology.

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Authors and Affiliations

  1. Computer Center, Shanghai University, Shanghai, 200444, People’s Republic of China

    Jun-Hua Duan

  2. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200072, People’s Republic of China

    Tao Meng & Quan-Ke Pan

  3. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, People’s Republic of China

    Qing-Da Chen

Authors
  1. Jun-Hua Duan
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  2. Tao Meng
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  3. Qing-Da Chen
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  4. Quan-Ke Pan
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Corresponding author

Correspondence to Quan-Ke Pan .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Indian Institute of Technology Madras, Chennai, India

    M. Michael Gromiha

  3. Inha University, Incheon, Korea (Republic of)

    Kyungsook Han

  4. Liverpool John Moores University, Liverpool, United Kingdom

    Abir Hussain

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Duan, JH., Meng, T., Chen, QD., Pan, QK. (2018). An Effective Artificial Bee Colony for Distributed Lot-Streaming Flowshop Scheduling Problem. In: Huang, DS., Gromiha, M., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science(), vol 10956. Springer, Cham. https://doi.org/10.1007/978-3-319-95957-3_84

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  • DOI: https://doi.org/10.1007/978-3-319-95957-3_84

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95956-6

  • Online ISBN: 978-3-319-95957-3

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