Computing non-stationary (s, S) policies using mixed integer linear programming

Mengyuan Xiang, Roberto Rossi, Belen Martin-Barragan and S. Armagan Tarim

European Journal of Operational Research, 2018, vol. 271, issue 2, 490-500

Abstract: This paper addresses the single-item single-stocking location non-stationary stochastic lot sizing problem under the (s, S) control policy. We first present a mixed integer non-linear programming (MINLP) formulation for determining near-optimal (s, S) policy parameters. To tackle larger instances, we then combine the previously introduced MINLP model and a binary search approach. These models can be reformulated as mixed integer linear programming (MILP) models which can be easily implemented and solved by using off-the-shelf optimization software. Computational experiments demonstrate that optimality gaps of these models are less than 0.3% of the optimal policy cost and computational times are reasonable.

Keywords: Inventory; (s, S) policy; Stochastic lot-sizing; Mixed integer programming; Binary search (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:271:y:2018:i:2:p:490-500

DOI: 10.1016/j.ejor.2018.05.030

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