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Rescheduling due to machine disruption to minimize the total weighted completion time

Author

Listed:
  • Wenchang Luo

    (Ningbo University
    University of Alberta)

  • Taibo Luo

    (University of Alberta
    Xidian University)

  • Randy Goebel

    (University of Alberta)

  • Guohui Lin

    (University of Alberta)

Abstract

We investigate a single machine rescheduling problem that arises from an unexpected machine unavailability, after the given set of jobs has already been scheduled to minimize the total weighted completion time. Such a disruption is represented as an unavailable time interval and is revealed to the production planner before any job is processed; the production planner wishes to reschedule the jobs to minimize the alteration to the originally planned schedule, which is measured as the maximum time deviation between the original and the new schedules for all the jobs. The objective function in this rescheduling problem is to minimize the sum of the total weighted completion time and the weighted maximum time deviation, under the constraint that the maximum time deviation is bounded above by a given value. That is, the maximum time deviation is taken both as a constraint and as part of the objective function. We present a pseudo-polynomial time exact algorithm and a fully polynomial time approximation scheme.

Suggested Citation

  • Wenchang Luo & Taibo Luo & Randy Goebel & Guohui Lin, 2018. "Rescheduling due to machine disruption to minimize the total weighted completion time," Journal of Scheduling, Springer, vol. 21(5), pages 565-578, October.
    • Handle: RePEc:spr:jsched:v:21:y:2018:i:5:d:10.1007_s10951-018-0575-z
    DOI: 10.1007/s10951-018-0575-z
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    References listed on IDEAS

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    Cited by:

    1. Chen, Rubing & Cheng, T.C.E. & Ng, C.T. & Wang, Jun-Qiang & Wei, Hongjun & Yuan, Jinjiang, 2024. "Rescheduling to trade off between global disruption of original jobs with flexibility and scheduling cost of new jobs," Omega, Elsevier, vol. 128(C).
    2. Xingong Zhang & Win-Chin Lin & Chin-Chia Wu, 2022. "Rescheduling problems with allowing for the unexpected new jobs arrival," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 630-645, April.
    3. Wenchang Luo & Rylan Chin & Alexander Cai & Guohui Lin & Bing Su & An Zhang, 2022. "A tardiness-augmented approximation scheme for rejection-allowed multiprocessor rescheduling," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 690-722, August.

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