A state space augmentation algorithm for the replenishment cycle inventory policy

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Rossi R., TARIM Ş. A., HNİCH B., Prestwich S.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, vol.133, no.1, pp.377-384, 2011 (SCI-Expanded) identifier identifier


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. (C) 2010 Elsevier B.V. All rights reserved.