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A Branch-and-Bound Algorithm for Two-Agent Scheduling with Learning Effect and Late Work Criterion

Author

Listed:
  • Shang-Chia Liu

    (Department of Business Administration, Fu Jen Catholic University, New Taipei City, 24205, Taiwan)

  • Jiahui Duan

    (Business School, Sichuan University, Chengdu 610064, P. R. China)

  • Win-Chin Lin

    (Department of Statistics, Feng-Chia University, Taichung 40724, Taiwan)

  • Wen-Hsiang Wu

    (Department of Healthcare Management, Yuanpei University of Medical Technology, Hsinchu 30015, Taiwan)

  • Jan-Yee Kung

    (Department of Business Administration, Cheng Shiu University, Kaohsiung 83347, Taiwan)

  • Hau Chen

    (Department of Statistics, Feng-Chia University, Taichung 40724, Taiwan)

  • Chin-Chia Wu

    (Department of Statistics, Feng-Chia University, Taichung 40724, Taiwan)

Abstract

This paper studies a two-agent single-machine scheduling problem with sum-of-processing-times-based learning consideration. The goal is to find an optimal schedule to minimize the total late work of the first agent subject to the restriction that the maximum lateness of the second agent has an upper bound. For this problem, a branch-and-bound algorithm along with several dominances and a lower bound is developed to find the optimal solution, and a tabu algorithm with several improvements is proposed to find the near-optimal solution. Computational experiments are provided to further measure the performance of the proposed algorithms.

Suggested Citation

  • Shang-Chia Liu & Jiahui Duan & Win-Chin Lin & Wen-Hsiang Wu & Jan-Yee Kung & Hau Chen & Chin-Chia Wu, 2018. "A Branch-and-Bound Algorithm for Two-Agent Scheduling with Learning Effect and Late Work Criterion," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(05), pages 1-24, October.
    • Handle: RePEc:wsi:apjorx:v:35:y:2018:i:05:n:s0217595918500379
    DOI: 10.1142/S0217595918500379
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    References listed on IDEAS

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    Cited by:

    1. Sterna, Małgorzata, 2021. "Late and early work scheduling: A survey," Omega, Elsevier, vol. 104(C).
    2. Chen, Xin & Liang, Yage & Sterna, Małgorzata & Wang, Wen & Błażewicz, Jacek, 2020. "Fully polynomial time approximation scheme to maximize early work on parallel machines with common due date," European Journal of Operational Research, Elsevier, vol. 284(1), pages 67-74.
    3. Shi-Sheng Li & Jin-Jiang Yuan, 2020. "Single-machine scheduling with multi-agents to minimize total weighted late work," Journal of Scheduling, Springer, vol. 23(4), pages 497-512, August.

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