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Single machine scheduling problem with stochastic sequence-dependent setup times

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  • Mehmet Ertem
  • Feristah Ozcelik
  • Tugba Saraç

Abstract

In this study, we consider stochastic single machine scheduling problem. We assume that setup times are both sequence dependent and uncertain while processing times and due dates are deterministic. In the literature, most of the studies consider the uncertainty on processing times or due dates. However, in the real-world applications (i.e. plastic moulding industry, appliance assembly, etc.), it is common to see varying setup times due to labour or setup tools availability. In order to cover this fact in machine scheduling, we set our objective as to minimise the total expected tardiness under uncertain sequence-dependent setup times. For the solution of this NP-hard problem, several heuristics and some dynamic programming algorithms have been developed. However, none of these approaches provide an exact solution for the problem. In this study, a two-stage stochastic-programming method is utilised for the optimal solution of the problem. In addition, a Genetic Algorithm approach is proposed to solve the large-size problems approximately. Finally, the results of the stochastic approach are compared with the deterministic one to demonstrate the value of the stochastic solution.

Suggested Citation

  • Mehmet Ertem & Feristah Ozcelik & Tugba Saraç, 2019. "Single machine scheduling problem with stochastic sequence-dependent setup times," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 3273-3289, May.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3273-3289
    DOI: 10.1080/00207543.2019.1581383
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    Cited by:

    1. Dönmez, Kadir & Çetek, Cem & Kaya, Onur, 2022. "Air traffic management in parallel-point merge systems under wind uncertainties," Journal of Air Transport Management, Elsevier, vol. 104(C).
    2. Mina Roohnavazfar & Daniele Manerba & Lohic Fotio Tiotsop & Seyed Hamid Reza Pasandideh & Roberto Tadei, 2021. "Stochastic single machine scheduling problem as a multi-stage dynamic random decision process," Computational Management Science, Springer, vol. 18(3), pages 267-297, July.
    3. Tugba Saraç & Feristah Ozcelik & Mehmet Ertem, 2023. "Unrelated parallel machine scheduling problem with stochastic sequence dependent setup times," Operational Research, Springer, vol. 23(3), pages 1-19, September.
    4. Zheng Wang & Jiuh‐Biing Sheu & Chung‐Piaw Teo & Guiqin Xue, 2022. "Robot Scheduling for Mobile‐Rack Warehouses: Human–Robot Coordinated Order Picking Systems," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 98-116, January.
    5. Lu, Haimin & Pei, Zhi, 2023. "Single machine scheduling with release dates: A distributionally robust approach," European Journal of Operational Research, Elsevier, vol. 308(1), pages 19-37.

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