Integrated planning of spare parts and service engineers with partial backlogging

S. Rahimi-Ghahroodi, A. Al Hanbali, W. H.M. Zijm, J. K.W. van Ommeren, A. Sleptchenko

    Research output: Contribution to journalArticlepeer-review

    12 Scopus citations


    In this paper, we consider the integrated planning of resources in a service maintenance logistics system in which spare parts supply and service engineers deployment are considered simultaneously. The objective is to determine close-to-optimal stock levels as well as the number of service engineers that minimize the total average costs under a maximum total average waiting time constraint. When a failure occurs, a spare part and a service engineer are requested for the repair call. In case of a stock-out at spare parts inventory, the repair call will be satisfied entirely via an emergency channel with a fast replenishment time but at a high cost. However, if the requested spare part is in stock, the backlogging policy is followed for engineers. We model the problem as a queueing network. An exact method and two approximations for the evaluation of a given policy are presented. We exploit evaluation methods in a greedy heuristic procedure to optimize this integrated planning. In a numerical study, we show that for problems with more than five types of spare parts it is preferable to use approximate evaluations as they become significantly faster than exact evaluation. Moreover, approximation errors decrease as problems get larger. Furthermore, we test how the greedy optimization heuristic performs compared to other discrete search algorithms in terms of total costs and computation times. Finally, in a rather large case study, we show that we may incur up to 27% cost savings when using the integrated planning as compared to a separated optimization.

    Original languageBritish English
    Pages (from-to)711-748
    Number of pages38
    JournalOR Spectrum
    Issue number3
    StatePublished - 1 Jul 2017


    • Approximate evaluation
    • Field service
    • Heuristic optimization
    • Maintenance logistics
    • Queueing
    • Spare parts inventory


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