Rossi R.Armagan Tarim S.Hnich B.Prestwich S.2023-06-162023-06-162007354072396X97835407239670302-9743https://doi.org/10.1007/978-3-540-72397-4_17https://hdl.handle.net/20.500.14365/33924th International Conference on Integration of Artificial Intelligence, Constraint Programming, and Operations Research Techniques for Combinatorial Optimization Problems, CPAIOR 2007 -- 23 May 2007 through 26 May 2007 -- Brussels -- 70750One of the most important policies adopted in inventory control is the (R,S) policy (also known as the "replenishment cycle" policy). Under the non-stationary demand assumption the (R,S) policy takes the form (R n,Sn) where Rn denotes the length of the n th replenishment cycle, and Sn the corresponding order-up-to-level. Such a policy provides an effective means of damping planning instability and coping with demand uncertainty. In this paper we develop a CP approach able to compute optimal (Rn,Sn) policy parameters under stochastic demand, ordering, holding and shortage costs. The convexity of the cost-function is exploited during the search to compute bounds. We use the optimal solutions to analyze the quality of the solutions provided by an approximate MIP approach that exploits a piecewise linear approximation for the cost function. © Springer-Verlag Berlin Heidelberg 2007.eninfo:eu-repo/semantics/openAccessCost functionsCostsDecision makingProcess planningRandom processesUncertainty analysisDemand assumptionDemand uncertaintyPolicy parametersReplenishment planningInventory controlConference Object10.1007/978-3-540-72397-4_172-s2.0-37149045708