Constraint programming for stochastic inventory systems under shortage cost

Constraint programming for stochastic inventory systems under shortage cost

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Article ID: iaor20123437
Volume: 195
Issue: 1
Start Page Number: 49
End Page Number: 71
Publication Date: May 2012
Journal: Annals of Operations Research
Authors: , , ,
Keywords: simulation: applications, combinatorial optimization
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.

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