Cost-Based Filtering for Stochastic Inventory Control

  • S. Armagan Tarim
  • Brahim Hnich
  • Roberto Rossi
  • Steven Prestwich
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4651)


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.


Optimal Policy Planning Horizon Constraint Programming Constraint Satisfaction Problem Dijkstra Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • S. Armagan Tarim
    • 1
  • Brahim Hnich
    • 2
  • Roberto Rossi
    • 3
  • Steven Prestwich
    • 3
  1. 1.Department of Management, Hacettepe UniversityTurkey
  2. 2.Faculty of Computer Science, Izmir University of EconomicsTurkey
  3. 3.Cork Constraint Computation Centre, University College, CorkIreland

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