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Scheduling policies for a repair shop problem

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  • William Liang
  • Barış Balcıog̃lu
  • Robert Svaluto

Abstract

In this paper, we analyze a repair shop serving several fleets of machines that fail from time to time. To reduce downtime costs, a continuous-review spare machine inventory is kept for each fleet. A spare machine, if available on stock, is installed instantaneously in place of a broken machine. When a repaired machine is returned from the repair shop, it is placed in inventory for future use if the fleet has the required number of machines operating. Since the repair shop is shared by different fleets, choosing which type of broken machine to repair is crucial to minimize downtime and holding costs. The optimal policy of this problem is difficult to characterize, and, therefore, is only formulated as a Markov Decision Process to numerically compute the optimal cost and base-stock level for each spare machine inventory. As an alternative, we propose the dynamic Myopic( R) policy, which is easy to implement, yielding costs very close to the optimal. Most of the time it outperforms the static first-come-first-served, and preemptive-resume priority policies. Additionally, via our numerical study, we demonstrate that repair shop pooling is better than reserving a repair shop for each fleet. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • William Liang & Barış Balcıog̃lu & Robert Svaluto, 2013. "Scheduling policies for a repair shop problem," Annals of Operations Research, Springer, vol. 211(1), pages 273-288, December.
    • Handle: RePEc:spr:annopr:v:211:y:2013:i:1:p:273-288:10.1007/s10479-013-1412-6
    DOI: 10.1007/s10479-013-1412-6
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    Cited by:

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    5. Topan, E. & Eruguz, A.S. & Ma, W. & van der Heijden, M.C. & Dekker, R., 2020. "A review of operational spare parts service logistics in service control towers," European Journal of Operational Research, Elsevier, vol. 282(2), pages 401-414.

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