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Two-agent scheduling on bounded parallel-batching machines with an aging effect of job-position-dependent

Author

Listed:
  • Jun Pei

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education
    University of Florida)

  • Jinling Wei

    (Hefei University of Technology)

  • Baoyu Liao

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education)

  • Xinbao Liu

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education)

  • Panos M. Pardalos

    (University of Florida)

Abstract

This paper investigates a competitive two-agent parallel-batching scheduling problem with aging effect on parallel machines. The objective is to minimize the makespan of agent A with the constraint that the makespan of agent B is no more than a given threshold. Some key structural properties are first identified in two different cases, and based on these structural properties a novel decision tree of scheduling rules is constructed and a heuristic algorithm is designed. Then, an effective hybrid BF-VNS algorithm combining Bacterial Foraging (BF) with variable neighborhood search (VNS) is developed to tackle the studied problem. Computational experiments are conducted to evaluate the performance of the proposed hybrid algorithm and some other well-known algorithms. The experimental results indicate that the hybrid BF-VNS algorithm performs quite better than the compared algorithms.

Suggested Citation

  • Jun Pei & Jinling Wei & Baoyu Liao & Xinbao Liu & Panos M. Pardalos, 2020. "Two-agent scheduling on bounded parallel-batching machines with an aging effect of job-position-dependent," Annals of Operations Research, Springer, vol. 294(1), pages 191-223, November.
    • Handle: RePEc:spr:annopr:v:294:y:2020:i:1:d:10.1007_s10479-019-03160-y
    DOI: 10.1007/s10479-019-03160-y
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    References listed on IDEAS

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