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Allocating spares to maximize the window fill rate in a periodic review inventory system

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  • Dreyfuss, Michael
  • Giat, Yahel

Abstract

We study the spares allocation problem in a multiple-item, multiple-location inventory system with periodic review. The system allocates spares with the objective of maximizing the window fill rate, which is the probability that a random customer is served within a given time window. The advantage of the window fill rate as a service performance measure is that it takes into account that customers may tolerate a certain wait before they are served. We develop the window fill rate formula and show that, depending on the tolerable wait, it is either a constant, concave or convex-concave with the number of spares. We use this result to develop an efficient algorithm to find the optimal spares allocation for a given budget or for a given target window fill rate. We show that when the tolerable wait or the budget are small, spares will be clustered in a subgroup of the locations (or item-types), while the other locations (or item-types) do not receive any spares. In addition, we numerically illustrate the spares allocation problem using two different synthetic large-scale examples. In particular, we use these examples to demonstrate the cost (in terms of additional spares) of a periodic review compared to a continuous review. The numerical illustration also highlights the complexity of the window fill rate and the savings gained by using it as an optimality criterion.

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  • Dreyfuss, Michael & Giat, Yahel, 2019. "Allocating spares to maximize the window fill rate in a periodic review inventory system," International Journal of Production Economics, Elsevier, vol. 214(C), pages 151-162.
    • Handle: RePEc:eee:proeco:v:214:y:2019:i:c:p:151-162
    DOI: 10.1016/j.ijpe.2019.04.017
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