Article ID: | iaor20116530 |
Volume: | 133 |
Issue: | 1 |
Start Page Number: | 377 |
End Page Number: | 384 |
Publication Date: | Sep 2011 |
Journal: | International Journal of Production Economics |
Authors: | Prestwich Steven, Hnich Brahim, Tarim S Armagan, Rossi Roberto |
Keywords: | programming: dynamic |
In this work we propose an efficient dynamic programming approach for computing replenishment cycle policy parameters under non‐stationary stochastic demand and service level constraints. The replenishment cycle policy is a popular inventory control policy typically employed for dampening planning instability. The approach proposed in this work achieves a significant computational efficiency and it can solve any relevant size instance in trivial time. Our method exploits the well known concept of state space relaxation. A filtering procedure and an augmenting procedure for the state space graph are proposed. Starting from a relaxed state space graph our method tries to remove provably suboptimal arcs and states (filtering) and then it tries to efficiently build up (augmenting) a reduced state space graph representing the original problem. Our experimental results show that the filtering procedure and the augmenting procedure often generate a small filtered state space graph, which can be easily processed using dynamic programming in order to produce a solution for the original problem.