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Job-shop scheduling problem with energy consideration

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  • Masmoudi, Oussama
  • Delorme, Xavier
  • Gianessi, Paolo

Abstract

These days, rising energy costs along with general concerns about major environmental issues (global warming, climate change), result in more and more strict production constraints for the industrial sector, which is known to be the first energy consumer and greenhouse gas emitter in the world. There is therefore a growing industrial need to address the problems of production systems related to energy aspects.

Suggested Citation

  • Masmoudi, Oussama & Delorme, Xavier & Gianessi, Paolo, 2019. "Job-shop scheduling problem with energy consideration," International Journal of Production Economics, Elsevier, vol. 216(C), pages 12-22.
    • Handle: RePEc:eee:proeco:v:216:y:2019:i:c:p:12-22
    DOI: 10.1016/j.ijpe.2019.03.021
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    References listed on IDEAS

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    5. Liu, Ying & Dong, Haibo & Lohse, Niels & Petrovic, Sanja, 2016. "A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance," International Journal of Production Economics, Elsevier, vol. 179(C), pages 259-272.
    6. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.
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    Citations

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    Cited by:

    1. Annear, Luis Mauricio & Akhavan-Tabatabaei, Raha & Schmid, Verena, 2023. "Dynamic assignment of a multi-skilled workforce in job shops: An approximate dynamic programming approach," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1109-1125.
    2. Rami Naimi & Maroua Nouiri & Olivier Cardin, 2021. "A Q-Learning Rescheduling Approach to the Flexible Job Shop Problem Combining Energy and Productivity Objectives," Sustainability, MDPI, vol. 13(23), pages 1-36, November.
    3. Tian, Zheng & Zheng, Li, 2024. "Single machine parallel-batch scheduling under time-of-use electricity prices: New formulations and optimisation approaches," European Journal of Operational Research, Elsevier, vol. 312(2), pages 512-524.
    4. Ivan Ferretti & Matteo Camparada & Lucio Enrico Zavanella, 2022. "Queuing Theory-Based Design Methods for the Definition of Power Requirements in Manufacturing Systems," Energies, MDPI, vol. 15(20), pages 1-14, October.
    5. Min Dai & Ziwei Zhang & Adriana Giret & Miguel A. Salido, 2019. "An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints," Sustainability, MDPI, vol. 11(11), pages 1-23, May.
    6. Sinisterra, Wilfrido Quiñones & Cavalcante, Cristiano Alexandre Virgínio, 2020. "An integrated model of production scheduling and inspection planning for resumable jobs," International Journal of Production Economics, Elsevier, vol. 227(C).
    7. Park, Myoung-Ju & Ham, Andy, 2022. "Energy-aware flexible job shop scheduling under time-of-use pricing," International Journal of Production Economics, Elsevier, vol. 248(C).
    8. Xiangxin An & Guojin Si & Tangbin Xia & Qinming Liu & Yaping Li & Rui Miao, 2022. "Operation and Maintenance Optimization for Manufacturing Systems with Energy Management," Energies, MDPI, vol. 15(19), pages 1-19, October.
    9. João M. R. C. Fernandes & Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2022. "Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review," Sustainability, MDPI, vol. 14(10), pages 1-34, May.
    10. Delorme, Xavier & Cerqueus, Audrey & Gianessi, Paolo & Lamy, Damien, 2023. "RMS balancing and planning under uncertain demand and energy cost considerations," International Journal of Production Economics, Elsevier, vol. 261(C).

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