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Idle time and capacity control for a single machine scheduling problem with dynamic electricity pricing

Author

Listed:
  • Seokgi Lee

    (University of Miami)

  • Mona Issabakhsh

    (University of Miami)

  • Hyun Woo Jeon

    (Louisiana State University)

  • Seong Wook Hwang

    (Hongik University)

  • Byung Chung

    (Yonsei University)

Abstract

In this paper, we develop a dynamic control algorithm for production scheduling that considers machine capacity and idle time controls and aims at satisfying time related production demand and reducing energy consumption in a unified manner. A mixed integer nonlinear programming (MINLP) model is developed to determine job arrival sequence for a machine and machine capacity while minimizing resulting costs of just-in-time production, machine repair, and energy consumption during machine idle time and nominal processing. A dynamic control algorithm based on feedback control of continuous variables is also developed to determine an energy-efficient production schedule with proper machine capacity and turn-off schedules. Energy, JIT, and maintenance costs of the proposed approach are examined using real energy and machining parameters of a HAAS VF0 milling machine. Algorithmic performance of the proposed dynamic control approach is compared to other heuristics, adaptive large neighborhood search (ALNS), and genetic algorithm (GA) with a speed optimization (SO) component. Experimental results show that the proposed algorithm improved performance by an average 10.0 ~ 93.8% and 0.52 ~ 22.9% compared to GA and ALNS with the SO module, respectively.

Suggested Citation

  • Seokgi Lee & Mona Issabakhsh & Hyun Woo Jeon & Seong Wook Hwang & Byung Chung, 2020. "Idle time and capacity control for a single machine scheduling problem with dynamic electricity pricing," Operations Management Research, Springer, vol. 13(3), pages 197-217, December.
    • Handle: RePEc:spr:opmare:v:13:y:2020:i:3:d:10.1007_s12063-020-00156-x
    DOI: 10.1007/s12063-020-00156-x
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    References listed on IDEAS

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    1. 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.
    2. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    3. Luo, Hao & Du, Bing & Huang, George Q. & Chen, Huaping & Li, Xiaolin, 2013. "Hybrid flow shop scheduling considering machine electricity consumption cost," International Journal of Production Economics, Elsevier, vol. 146(2), pages 423-439.
    4. Lusby, Richard Martin & Schwierz, Martin & Range, Troels Martin & Larsen, Jesper, 2016. "An Adaptive Large Neighbourhood Search Procedure Applied to the Dynamic Patient Admission Scheduling Problem," Discussion Papers on Economics 1/2016, University of Southern Denmark, Department of Economics.
    5. Kan Fang & Nelson A. Uhan & Fu Zhao & John W. Sutherland, 2016. "Scheduling on a single machine under time-of-use electricity tariffs," Annals of Operations Research, Springer, vol. 238(1), pages 199-227, March.
    6. 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.
    7. Kan Fang & Nelson Uhan & Fu Zhao & John Sutherland, 2016. "Scheduling on a single machine under time-of-use electricity tariffs," Annals of Operations Research, Springer, vol. 238(1), pages 199-227, March.
    8. Zhiyang Jia & Liang Zhang & Jorge Arinez & Guoxian Xiao, 2016. "Performance analysis for serial production lines with Bernoulli Machines and Real-time WIP-based Machine switch-on/off control," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6285-6301, November.
    9. Guo-Sheng Liu & Hai-Dong Yang & Ming-Bao Cheng, 2017. "A three-stage decomposition approach for energy-aware scheduling with processing-time-dependent product quality," International Journal of Production Research, Taylor & Francis Journals, vol. 55(11), pages 3073-3091, June.
    10. Muller, Laurent Flindt & Spoorendonk, Simon & Pisinger, David, 2012. "A hybrid adaptive large neighborhood search heuristic for lot-sizing with setup times," European Journal of Operational Research, Elsevier, vol. 218(3), pages 614-623.
    11. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    12. Timo Gschwind & Michael Drexl, 2019. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 53(2), pages 480-491, March.
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