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Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions

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  • Pablo Valledor
  • Alberto Gomez
  • Paolo Priore
  • Javier Puente

Abstract

In multi-objective optimisation problems, optimal decisions need to be made in the presence of trade-offs among conflicting objectives which may sometimes be expressed in different units of measure. This makes it difficult to reduce the problem to a single-objective optimisation. Furthermore, when disruptive changes emerge in manufacturing environments, such as the arrival of new jobs or machine breakdowns, the scheduling system should be adapted by responding quickly. In this paper, we propose a rescheduling architecture for solving the problem based on a predictive-reactive strategy and a new method to calculate the reactive schedule in each rescheduling period. Additionally, we developed a methodology that allows the use of multi-objective performance metrics to evaluate dispatching rules. These rules are applied at a benchmark specifically designed for this paper considering three objective functions: makespan, total weighted tardiness and stability. Three types of disruptions are also considered: arrivals of new jobs, machine breakdowns and variations in job processing times. Results showed that the RANDOM rule provides a better behaviour compared to other evaluated rules and a lower ratio of non-dominated solutions compared to ATC (apparent tardiness cost) and FIFO (first-in-first-out) rules. Moreover, the behaviour of the hypervolume metric depends on the problem dimensions.

Suggested Citation

  • Pablo Valledor & Alberto Gomez & Paolo Priore & Javier Puente, 2018. "Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 56(19), pages 6363-6377, October.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:19:p:6363-6377
    DOI: 10.1080/00207543.2018.1468095
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    Cited by:

    1. Sofia Holguin Jimenez & Wajdi Trabelsi & Christophe Sauvey, 2024. "Multi-Objective Production Rescheduling: A Systematic Literature Review," Mathematics, MDPI, vol. 12(20), pages 1-31, October.
    2. Xinyu Sun & Xin-Na Geng & Tao Liu, 2020. "Due-window assignment scheduling in the proportionate flow shop setting," Annals of Operations Research, Springer, vol. 292(1), pages 113-131, September.
    3. Didden, Jeroen B.H.C. & Dang, Quang-Vinh & Adan, Ivo J.B.F., 2024. "Enhancing stability and robustness in online machine shop scheduling: A multi-agent system and negotiation-based approach for handling machine downtime in industry 4.0," European Journal of Operational Research, Elsevier, vol. 316(2), pages 569-583.
    4. Xingong Zhang & Win-Chin Lin & Chin-Chia Wu, 2022. "Rescheduling problems with allowing for the unexpected new jobs arrival," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 630-645, April.

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