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Single-machine scheduling with times-based and job-dependent learning effect

Author

Listed:
  • Zhongyi Jiang

    (Changzhou University
    School of Management, Fudan University)

  • Fangfang Chen

    (Changzhou University)

  • Xiandong Zhang

    (School of Management, Fudan University)

Abstract

Absract Learning effect is a phenomenon in industrial processes that a machine (plant, worker, etc) can improve its productivity continuously with time, that is the actual processing time of a job decreases after the machine (plant, worker, etc) processes other jobs and gains some experiences. We study single machine scheduling problems with sum-of-processing-time based and job-dependent learning effect. The objectives are to minimize the maximum lateness, the number of tardy jobs, and total weighted completion time. By performing reductions from equal cardinality partition problem, we prove that these problems under investigation are all NP-hard. Two special cases that can be solved in polynomial time are also presented.

Suggested Citation

  • Zhongyi Jiang & Fangfang Chen & Xiandong Zhang, 2017. "Single-machine scheduling with times-based and job-dependent learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 809-815, July.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:7:d:10.1057_jors.2016.40
    DOI: 10.1057/jors.2016.40
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    References listed on IDEAS

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    1. Baoyu Liao & Xingming Wang & Xing Zhu & Shanlin Yang & Panos M. Pardalos, 2020. "Less is more approach for competing groups scheduling with different learning effects," Journal of Combinatorial Optimization, Springer, vol. 39(1), pages 33-54, January.

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