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Energy-Aware Flexible Job Shop Scheduling Using Mixed Integer Programming and Constraint Programming

Author

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  • Andy Ham
  • Myoung-Ju Park
  • Kyung Min Kim

Abstract

Compromising productivity in exchange for energy saving does not appeal to highly capitalized manufacturing industries. However, we might be able to maintain the same productivity while significantly reducing energy consumption. This paper addresses a flexible job shop scheduling problem with a shutdown (on/off) strategy aiming to minimize makespan and total energy consumption. First, an alternative mixed integer linear programming model is proposed. Second, a novel constraint programming is proposed. Third, practical operational scenarios are compared. Finally, we provide benchmarking instances, CPLEX codes, and genetic algorithm codes, in order to promote related research, thus expediting the adoption of energy-efficient scheduling in manufacturing facilities. The computational study demonstrates that (1) the proposed models significantly outperform other benchmark models and (2) we can maintain maximum productivity while significantly reducing energy consumption by 14.85% (w/o shutdown) and 15.23% (w/shutdown) on average.

Suggested Citation

  • Andy Ham & Myoung-Ju Park & Kyung Min Kim, 2021. "Energy-Aware Flexible Job Shop Scheduling Using Mixed Integer Programming and Constraint Programming," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, June.
    • Handle: RePEc:hin:jnlmpe:8035806
    DOI: 10.1155/2021/8035806
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    Cited by:

    1. 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.
    2. Wen, Xuanhao & Cao, Huajun & Li, Hongcheng & Zheng, Jie & Ge, Weiwei & Chen, Erheng & Gao, Xi & Hon, Bernard, 2022. "A dual energy benchmarking methodology for energy-efficient production planning and operation of discrete manufacturing systems using data mining techniques," Energy, Elsevier, vol. 255(C).

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