A partial characterization of the optimal ordering/rationing policy for a periodic review system with two demand classes and backordering

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

10 Scopus Citations
View graph of relations

Author(s)

  • Shaoxiang Chen
  • Jianjun Xu
  • Youyi Feng

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)330-341
Journal / PublicationNaval Research Logistics
Volume57
Issue number4
Publication statusPublished - Jun 2010

Abstract

We consider a finite horizon periodic review, single product inventory system with a fixed setup cost and two stochastic demand classes that differ in their backordering costs. In each period, one must decide whether and how much to order, and how much demand of the lower class should be satisfied. We show that the optimal ordering policy can be characterized as a state dependent (s, S) policy, and the rationing structure is partially obtained based on the subconvexity of the cost function. We then propose a simple heuristic rationing policy, which is easy to implement and close to optimal for intensive numerical examples. We further study the case when the first demand class is deterministic and must be satisfied immediately. We show the optimality of the state dependent (s, S) ordering policy, and obtain additional rationing structural properties. Based on these properties, the optimal ordering and rationing policy for any state can be generated by finding the optimal policy of only a finite set of states, and for each state in this set, the optimal policy is obtained simply by choosing a policy from at most two alternatives. An efficient algorithm is then proposed. © 2010 Wiley Periodicals, Inc.

Research Area(s)

  • Dynamic programming, Inventory/rationing, Stochastic models