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Minimizing Total Idle Energy Consumption in the Permutation Flow Shop Scheduling Problem

Author

Listed:
  • Guo-Sheng Liu

    (School of Management, Guangdong University of Technology (Longdong Campus), 161 Yinglong Road, Guangzhou 510520, P. R. China)

  • Jin-Jin Li

    (School of Management, Guangdong University of Technology (Longdong Campus), 161 Yinglong Road, Guangzhou 510520, P. R. China)

  • Ying-Si Tang

    (School of Management, Guangdong University of Technology (Longdong Campus), 161 Yinglong Road, Guangzhou 510520, P. R. China)

Abstract

In this paper, we investigate the well-known permutation flow shop (PFS) scheduling problem with a particular objective, the minimization of total idle energy consumption of the machines. The problem considers the energy waste induced by the machine idling, in which the idle energy consumption is evaluated by the multiplication of the idle time and power level of each machine. Since the problem considered is NP-hard, theoretical results are given for several basic cases. For the two-machine case, we prove that the optimal schedule can be found by employing a relaxed Johnson’s algorithm within O(n2) time complexity. For the cases with multiple machines (not less than 3), we propose a novel NEH heuristic algorithm to obtain an approximate energy-saving schedule. The heuristic algorithms are validated by comparison with NEH on a typical PFS problem and a case study for tire manufacturing shows an energy consumption reduction of approximately 5% by applying the energy-saving scheduling and the proposed algorithms.

Suggested Citation

  • Guo-Sheng Liu & Jin-Jin Li & Ying-Si Tang, 2018. "Minimizing Total Idle Energy Consumption in the Permutation Flow Shop Scheduling Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-19, December.
    • Handle: RePEc:wsi:apjorx:v:35:y:2018:i:06:n:s0217595918500410
    DOI: 10.1142/S0217595918500410
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    References listed on IDEAS

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