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Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints

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  • Ghorbanzadeh, Masoumeh
  • Ranjbar, Mohammad

Abstract

In this paper, we investigate an energy-aware flow shop scheduling problem under sequence-dependent setup times, group scheduling, and renewable energy constraints. We aim to minimize the total energy cost dependent on time-of-use electricity tariffs. To this end, we develop two mixed-integer linear programming models, including a time-unit index model and a time-interval index model. Besides, we develop a decomposition-based heuristic algorithm to solve efficiently medium-size instances. Using extensive computational experiments, we show that the heuristic algorithm outperforms both developed models, and the time-interval index model indicates superior performance than the time-unit index model. Finally, we provide a set of sensitivity analyses and evaluation of economic performance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:307:y:2023:i:2:p:519-537
    DOI: 10.1016/j.ejor.2022.09.034
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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. Bozorgirad, Mir Abbas & Logendran, Rasaratnam, 2013. "Bi-criteria group scheduling in hybrid flowshops," International Journal of Production Economics, Elsevier, vol. 145(2), pages 599-612.
    3. Feng, Hanxin & Xi, Lifeng & Xiao, Lei & Xia, Tangbin & Pan, Ershun, 2018. "Imperfect preventive maintenance optimization for flexible flowshop manufacturing cells considering sequence-dependent group scheduling," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 218-229.
    4. Konstantin Biel & Fu Zhao & John W. Sutherland & Christoph H. Glock, 2018. "Flow shop scheduling with grid-integrated onsite wind power using stochastic MILP," International Journal of Production Research, Taylor & Francis Journals, vol. 56(5), pages 2076-2098, March.
    5. 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.
    6. Zhai, Y. & Biel, K. & Zhao, F. & Sutherland, J. W., 2017. "Dynamic scheduling of a flow shop with on-site wind generation for energy cost reduction under real time electricity pricing," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 87366, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Zhang, Hao & Cai, Jie & Fang, Kan & Zhao, Fu & Sutherland, John W., 2017. "Operational optimization of a grid-connected factory with onsite photovoltaic and battery storage systems," Applied Energy, Elsevier, vol. 205(C), pages 1538-1547.
    8. Biel, K. & Glock, C. H., 2016. "Systematic literature review of decision support models for energy-efficient production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83071, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Biel, K. & Zhao, F. & Sutherland, J. & Glock, C. H., 2018. "Flow shop scheduling with grid-integrated onsite wind power using stochastic MILP," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 88879, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. 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.
    11. Li, Shanling, 1997. "A hybrid two-stage flowshop with part family, batch production, major and minor set-ups," European Journal of Operational Research, Elsevier, vol. 102(1), pages 142-156, October.
    12. 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.
    13. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    14. Schaller, Jeffrey E. & Gupta, Jatinder N. D. & Vakharia, Asoo J., 2000. "Scheduling a flowline manufacturing cell with sequence dependent family setup times," European Journal of Operational Research, Elsevier, vol. 125(2), pages 324-339, September.
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