Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming
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Published version
Date
2021-01-13
Authors
Visentin, Andrea
Prestwich, Steven D.
Rossi, Roberto
Tarim, S. Armagan
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Published Version
Abstract
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.
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Keywords
Inventory , (R,s,S) policy , Demand uncertainty , Stochastic lot sizing
Citation
Visentin, A., Prestwich, S., Rossi, R. and Tarim, S. A. (2021) 'Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming', European Journal of Operational Research, doi: 10.1016/j.ejor.2021.01.012