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Permutation flow shop energy-efficient scheduling with a position-based learning effect

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  • Xu Xin
  • Qiangqiang Jiang
  • Cui Li
  • Sihang Li
  • Kang Chen

Abstract

Severe environmental problems have made green scheduling an emerging research hotspot. In this paper, a permutation flow shop energy-efficient scheduling problem that considers multiple criteria is investigated. The aim is to find the optimal job processing sequence and conveyor speed that minimise both the makespan and total energy consumption. In addition to two types of common criteria, namely, machine-based criterion (i.e. sequence-dependent setup time) and energy-based criteria (including both the transportation time control strategy and machine shutdown strategy), a human-based criterion (i.e. a position-based learning effect) is introduced. A bi-objective programming model is developed, and a multi-objective iterated greedy (MOIG) is designed to reach the Pareto front of the model. Considering that there are two types of decisions in the model (i.e. job sequence and conveyor speed), two algorithm alternatives are designed based on the job sequence and conveyor speed, respectively. Meanwhile, an acceptance criterion with advantages in terms of the convergence speed and solution diversity is proposed. Existing algorithms, including NSGA-II and MOEA/D, are introduced to evaluate the performance of the MOIG. The results emphasise the efficiency of the MOIG. Overall, the model and MOIG effectively improve the green efficiency of enterprises and can reasonably control operating costs.

Suggested Citation

  • Xu Xin & Qiangqiang Jiang & Cui Li & Sihang Li & Kang Chen, 2023. "Permutation flow shop energy-efficient scheduling with a position-based learning effect," International Journal of Production Research, Taylor & Francis Journals, vol. 61(2), pages 382-409, January.
    • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:2:p:382-409
    DOI: 10.1080/00207543.2021.2008041
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    Cited by:

    1. Massimo Bertolini & Francesco Leali & Davide Mezzogori & Cristina Renzi, 2023. "A Keyword, Taxonomy and Cartographic Research Review of Sustainability Concepts for Production Scheduling in Manufacturing Systems," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    2. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.

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