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Minimising total weighted earliness and tardiness penalties on identical parallel machines using a fast ruin-and-recreate algorithm

Author

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  • Shih-Wei Lin
  • Kuo-Ching Ying
  • Yen-I Chiang
  • Wen-Jie Wu

Abstract

This paper studies the scheduling problem of minimising total weighted earliness and tardiness penalties on identical parallel machines against a restrictive common due date. This problem is NP-hard in the strong sense and arises in many just-in-time production environments. A fast ruin-and-recreate (FR&R) algorithm is proposed to obtain high-quality solutions to this complex problem. The proposed FR&R algorithm is tested on a well-known set of benchmark test problems that are taken from the literature. Computational results provide evidence of the efficiency of FR&R, which consistently outperform existing algorithms when applied to benchmark instances. This work provides a viable alternative approach for efficiently solving this practical but complex scheduling problem.

Suggested Citation

  • Shih-Wei Lin & Kuo-Ching Ying & Yen-I Chiang & Wen-Jie Wu, 2016. "Minimising total weighted earliness and tardiness penalties on identical parallel machines using a fast ruin-and-recreate algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(22), pages 6879-6890, November.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:22:p:6879-6890
    DOI: 10.1080/00207543.2016.1190041
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    Cited by:

    1. Zhen Wang & Qianwang Deng & Like Zhang & Xiaoyan Liu, 2023. "Integrated scheduling of production, inventory and imperfect maintenance based on mutual feedback of supplier and demander in distributed environment," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3445-3467, December.

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