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Bad-scenario-set robust scheduling for a job shop to hedge against processing time uncertainty

Author

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  • Bing Wang
  • Xiaozhi Wang
  • Hanxin Xie

Abstract

This paper proposed two robust scheduling formulations in real manufacturing systems based on the concept of bad scenario set to hedge against processing time uncertainty, which is described by discrete scenarios. Two proposed robust scheduling formulations are applied to an uncertain job-shop scheduling problem with the makespan as the performance criterion. The united-scenario neighbourhood (UN) structure is constructed based on bad scenario set for the scenario job-shop scheduling problem. A tabu search (TS) algorithm with the UN structure is developed to solve the proposed robust scheduling problem. An extensive experiment was conducted. The computational results show that the first robust scheduling formulation could be preferred to the second one for the discussed problem. It is also verified that the obtained robust solutions could hedge against the processing time uncertainty through decreasing the number of bad scenarios and the degree of performance degradation on bad scenarios. Moreover, the computational results demonstrate that the developed TS algorithm is competitive for the proposed robust scheduling formulations.

Suggested Citation

  • Bing Wang & Xiaozhi Wang & Hanxin Xie, 2019. "Bad-scenario-set robust scheduling for a job shop to hedge against processing time uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 3168-3185, May.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3168-3185
    DOI: 10.1080/00207543.2018.1555650
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    Cited by:

    1. Shabtay, Dvir & Gilenson, Miri, 2023. "A state-of-the-art survey on multi-scenario scheduling," European Journal of Operational Research, Elsevier, vol. 310(1), pages 3-23.
    2. Anran Zhao & Peng Liu & Xiyu Gao & Guotai Huang & Xiuguang Yang & Yuan Ma & Zheyu Xie & Yunfeng Li, 2022. "Data-Mining-Based Real-Time Optimization of the Job Shop Scheduling Problem," Mathematics, MDPI, vol. 10(23), pages 1-30, December.

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