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The energy scheduling problem: Industrial case-study and constraint propagation techniques

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  • Artigues, Christian
  • Lopez, Pierre
  • Haït, Alain

Abstract

This paper deals with production scheduling involving energy constraints, typically electrical energy. We start by an industrial case-study for which we propose a two-step integer/constraint programming method. From the industrial problem we derive a generic problem, the Energy Scheduling Problem (EnSP). We propose an extension of specific resource constraint propagation techniques to efficiently prune the search space for EnSP solving. We also present a branching scheme to solve the problem via tree search. Finally, computational results are provided.

Suggested Citation

  • Artigues, Christian & Lopez, Pierre & Haït, Alain, 2013. "The energy scheduling problem: Industrial case-study and constraint propagation techniques," International Journal of Production Economics, Elsevier, vol. 143(1), pages 13-23.
    • Handle: RePEc:eee:proeco:v:143:y:2013:i:1:p:13-23
    DOI: 10.1016/j.ijpe.2010.09.030
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sven Schulz & Udo Buscher & Liji Shen, 2020. "Multi-objective hybrid flow shop scheduling with variable discrete production speed levels and time-of-use energy prices," Journal of Business Economics, Springer, vol. 90(9), pages 1315-1343, November.
    2. Zanoni, Simone & Bettoni, Laura & Glock, Christoph H., 2014. "Energy implications in a two-stage production system with controllable production rates," International Journal of Production Economics, Elsevier, vol. 149(C), pages 164-171.
    3. Aghelinejad, MohammadMohsen & Ouazene, Yassine & Yalaoui, Alice, 2019. "Complexity analysis of energy-efficient single machine scheduling problems," Operations Research Perspectives, Elsevier, vol. 6(C).
    4. Margaux Nattaf & Christian Artigues & Pierre Lopez & David Rivreau, 2016. "Energetic reasoning and mixed-integer linear programming for scheduling with a continuous resource and linear efficiency functions," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 459-492, March.
    5. Lee, Cheng-Hsiung & Liao, Ching-Jong & Chung, Tsui-Ping, 2014. "Scheduling with multi-attribute setup times on two identical parallel machines," International Journal of Production Economics, Elsevier, vol. 153(C), pages 130-138.
    6. 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.
    7. Rapine, Christophe & Goisque, Guillaume & Akbalik, Ayse, 2018. "Energy-aware lot sizing problem: Complexity analysis and exact algorithms," International Journal of Production Economics, Elsevier, vol. 203(C), pages 254-263.
    8. 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.
    9. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    10. Roland Braune, 2022. "Packing-based branch-and-bound for discrete malleable task scheduling," Journal of Scheduling, Springer, vol. 25(6), pages 675-704, December.
    11. Beck, Fabian G. & Biel, Konstantin & Glock, Christoph H., 2019. "Integration of energy aspects into the economic lot scheduling problem," International Journal of Production Economics, Elsevier, vol. 209(C), pages 399-410.
    12. Stefan Bugow & Carolin Kellenbrink, 2023. "The parcel hub scheduling problem with limited conveyor capacity and controllable unloading speeds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 325-357, June.
    13. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    14. 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.
    15. Otashu, Joannah I. & Baldea, Michael, 2018. "Grid-level “battery” operation of chemical processes and demand-side participation in short-term electricity markets," Applied Energy, Elsevier, vol. 220(C), pages 562-575.
    16. Rapine, Christophe & Penz, Bernard & Gicquel, Céline & Akbalik, Ayse, 2018. "Capacity acquisition for the single-item lot sizing problem under energy constraints," Omega, Elsevier, vol. 81(C), pages 112-122.
    17. Ilia Tarasov & Alain Haït & Alexander Lazarev & Olga Battaïa, 2024. "Metric estimation approach for managing uncertainty in resource leveling problem," Annals of Operations Research, Springer, vol. 338(1), pages 645-673, July.
    18. Ramin, D. & Spinelli, S. & Brusaferri, A., 2018. "Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process," Applied Energy, Elsevier, vol. 225(C), pages 622-636.

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