Constraint programming for stochastic inventory systems under shortage cost

R. Rossi, S. Armagan Tarim, Brahim Hnich, Steven Prestwich

Research output: Contribution to journalArticlepeer-review

Abstract

One of the most important policies adopted in inventory control is the replenishment cycle policy. Such a policy provides an effective means of damping planning instability and coping with demand uncertainty. In this paper we develop a constraint programming approach able to compute optimal replenishment cycle policy parameters under non-stationary stochastic demand, ordering, holding and shortage costs. We show how in our model it is possible to exploit the convexity of the cost-function during the search to dynamically compute bounds and perform cost-based filtering. Our computational experience show the effectiveness of our approach. Furthermore, we use the optimal solutions to analyze the quality of the solutions provided by an existing approximate mixed integer programming approach that exploits a piecewise linear approximation for the cost function.
Original languageEnglish
Pages (from-to)49-71
Number of pages23
JournalAnnals of Operations Research
Volume195
Issue number1
Early online date29 Jul 2011
DOIs
Publication statusPublished - 29 Jul 2012

Keywords

  • Inventory control
  • Constraint programming
  • Decision making under uncertainty
  • Replenishment cycle policy
  • Non-stationary demand
  • Shortage cost

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