Computing optimal (R, s, S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming
Refereed Original Article
A well-known control policy in stochastic inventory control is the policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls below reorder-level s. To date, little or no work has been devoted to developing approaches for computing policy parameters. In this work, we introduce a hybrid approach that exploits tree search to compute optimal replenishment cycles, and stochastic dynamic programming to compute levels for a given cycle. Up to 99.8% of the search tree is pruned by a branch-and-bound technique with bounds generated by dynamic programming. A numerical study shows that the method can solve instances of realistic size in a reasonable time.
Digital Object Identifer (DOI):
European Journal of Operational Research
National University of Ireland, Cork (UCC)
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