Cost-Based Filtering for Stochastic Inventory Control

Abstract. An interesting class of production/inventory control problems considers a single product and a single stocking location, given a stochastic demand with a known non-stationary probability distribution. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using a cost-based filtering method. Our algorithm can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all.

• Type: Conference
• Year: 2006
• Where: CSCLP
• Authors: Armagan Tarim, Brahim Hnich, Roberto Rossi, Steven David Prestwich
• Keywords: Artificial Intelligence, CSCLP 2006, Non-stationary Probability Distribution, Single Stocking Location, Widely-used Control Policy