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A Branch-and-Bound Algorithm for Minimizing the Energy Consumption in the PFS Problem

Author

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  • Guo-Sheng Liu
  • Bi-Xi Zhang
  • Hai-Dong Yang
  • Xin Chen
  • George Q. Huang

Abstract

This paper considers the energy consumption minimization in permutation flow shop (PFS) scheduling problem. The energy consumption of each machine is decomposed into two parts: useful part which completes the operation at current stage and wasted part which is consumed during idle period. The objective considered here is to minimize the total wasted energy consumption which is a weighted summation of the idle time of each machine. To solve this new problem, a branch-and-bound algorithm is developed. Two lower bounds are proposed, and an initial upper bound by using a variant of NEH heuristic algorithm is applied. Compared with the makespan minimization criterion, this model deduces more energy-saving solutions. Experimental results also validate the efficiency of the proposed algorithm for problems with job number not larger than 15.

Suggested Citation

  • Guo-Sheng Liu & Bi-Xi Zhang & Hai-Dong Yang & Xin Chen & George Q. Huang, 2013. "A Branch-and-Bound Algorithm for Minimizing the Energy Consumption in the PFS Problem," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-6, March.
    • Handle: RePEc:hin:jnlmpe:546810
    DOI: 10.1155/2013/546810
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    Cited by:

    1. Fei Luan & Zongyan Cai & Shuqiang Wu & Shi Qiang Liu & Yixin He, 2019. "Optimizing the Low-Carbon Flexible Job Shop Scheduling Problem with Discrete Whale Optimization Algorithm," Mathematics, MDPI, vol. 7(8), pages 1-17, August.
    2. Tianhua Jiang & Chao Zhang & Huiqi Zhu & Jiuchun Gu & Guanlong Deng, 2018. "Energy-Efficient Scheduling for a Job Shop Using an Improved Whale Optimization Algorithm," Mathematics, MDPI, vol. 6(11), pages 1-16, October.

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