Capacity reservation and utilization for a manufacturer with uncertain capacity and demand

Y. Boulaksil, J.C. Fransoo, T. Tan

Research output: Contribution to journalArticleScientificpeer-review

Abstract

We consider an original equipment manufacturer (OEM) who has outsourced the production activities to a contract manufacturer (CM). The CM produces for multiple OEMs on the same capacitated production line. The CM requires that all OEMs reserve capacity slots before ordering and responds to these reservations by acceptance or partial rejection, based on allocation rules that are unknown to the OEM. Therefore, the allocated capacity for the OEM is not known in advance, also because the OEM has no information about the reservations of the other OEMs. Based on a real-life situation, we study this problem from the OEM’s perspective who faces stochastic demand and stochastic capacity allocation from the contract manufacturer. We model this problem as a single-item, periodic review inventory system, and we assume linear inventory holding, backorder, and reservation costs. We develop a stochastic dynamic programming model, and we characterize the optimal policy. We conduct a numerical study where we also consider the case that the capacity allocation is dependent on the demand distribution. The results show that the optimal reservation policy is little sensitive to the uncertainty of capacity allocation. In that case, the optimal reservation quantities hardly increase, but the optimal policy suggests increasing the utilization of the allocated capacity. Further, in comparison with a static policy, we show that a dynamic reservation policy is particularly useful when backorder cost and uncertainty are low. Moreover, we show that for the contract manufacturer, to achieve the desired behavior, charging little reservation costs is sufficient.
Original languageEnglish
Pages (from-to)689-709
Number of pages21
JournalOR Spektrum
Volume39
Issue number3
DOIs
Publication statusPublished - 1 Jul 2017

Keywords

  • Capacity reservation
  • Outsourcing
  • Stochastic capacity and demand
  • Stochastic dynamic programming

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