IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v13y2020i3d10.1007_s12063-020-00156-x.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-020-00156-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12063-020-00156-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Heydar, Mojtaba & Mardaneh, Elham & Loxton, Ryan, 2022. "Approximate dynamic programming for an energy-efficient parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 363-380.
    2. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2023. "Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1091-1109.
    3. Shen, Liji & Dauzère-Pérès, Stéphane & Maecker, Söhnke, 2023. "Energy cost efficient scheduling in flexible job-shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 310(3), pages 992-1016.
    4. 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.
    5. TURKEŠ, Renata & SÖRENSEN, Kenneth & HVATTUM, Lars Magnus & BARRENA, Eva & CHENTLI, Hayet & COELHO, Leandro & DAYARIAN, Iman & GRIMAULT, Axel & GULLHAVE, Anders & IRIS, Çagatay & KESKIN, Merve & KIEFE, 2019. "Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search," Working Papers 2019002, University of Antwerp, Faculty of Business and Economics.
    6. Turkeš, Renata & Sörensen, Kenneth & Hvattum, Lars Magnus, 2021. "Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search," European Journal of Operational Research, Elsevier, vol. 292(2), pages 423-442.
    7. Ghorbanzadeh, Masoumeh & Ranjbar, Mohammad, 2023. "Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints," European Journal of Operational Research, Elsevier, vol. 307(2), pages 519-537.
    8. Vadlamani, Satish & Hosseini, Seyedmohsen, 2014. "A novel heuristic approach for solving aircraft landing problem with single runway," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 144-148.
    9. Dumez, Dorian & Lehuédé, Fabien & Péton, Olivier, 2021. "A large neighborhood search approach to the vehicle routing problem with delivery options," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 103-132.
    10. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.
    11. Michal Penn & Tal Raviv, 2021. "Complexity and algorithms for min cost and max profit scheduling under time-of-use electricity tariffs," Journal of Scheduling, Springer, vol. 24(1), pages 83-102, February.
    12. 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.
    13. Si, Jinhua & He, Fang & Lin, Xi & Tang, Xindi, 2024. "Vehicle dispatching and routing of on-demand intercity ride-pooling services: A multi-agent hierarchical reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    14. Matthias Gerhard Wichmann & Christoph Johannes & Thomas Stefan Spengler, 2019. "An extension of the general lot-sizing and scheduling problem (GLSP) with time-dependent energy prices," Journal of Business Economics, Springer, vol. 89(5), pages 481-514, July.
    15. Gaggero, Mauro & Paolucci, Massimo & Ronco, Roberto, 2023. "Exact and heuristic solution approaches for energy-efficient identical parallel machine scheduling with time-of-use costs," European Journal of Operational Research, Elsevier, vol. 311(3), pages 845-866.
    16. Peng Wu & Junheng Cheng & Feng Chu, 2021. "Large-scale energy-conscious bi-objective single-machine batch scheduling under time-of-use electricity tariffs via effective iterative heuristics," Annals of Operations Research, Springer, vol. 296(1), pages 471-494, January.
    17. Wang, Yuan & Lei, Linfei & Zhang, Dongxiang & Lee, Loo Hay, 2020. "Towards delivery-as-a-service: Effective neighborhood search strategies for integrated delivery optimization of E-commerce and static O2O parcels," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 38-63.
    18. Perumal, Shyam S.G. & Larsen, Jesper & Lusby, Richard M. & Riis, Morten & Sørensen, Kasper S., 2019. "A matheuristic for the driver scheduling problem with staff cars," European Journal of Operational Research, Elsevier, vol. 275(1), pages 280-294.
    19. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2021. "Job Scheduling under Time-of-Use Energy Tariffs for Sustainable Manufacturing: A Survey," LIDAM Discussion Papers CORE 2021019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Hongliang Zhang & Yujuan Wu & Ruilin Pan & Gongjie Xu, 2021. "Two-stage parallel speed-scaling machine scheduling under time-of-use tariffs," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 91-112, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opmare:v:13:y:2020:i:3:d:10.1007_s12063-020-00156-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.