Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming

Andrea Visentin, Steven Prestwich, Roberto Rossi and S. Armagan Tarim

European Journal of Operational Research, 2021, vol. 294, issue 1, 91-99

Abstract: A well-known control policy in stochastic inventory control is the (R,s,S) 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 (R,s,S) 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 (s,S) 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.

Keywords: Inventory; (R,s,S) policy; Demand uncertainty; Stochastic lot sizing (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:294:y:2021:i:1:p:91-99

DOI: 10.1016/j.ejor.2021.01.012

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