Xiang, MengyuanRossi, RobertoMartin-Barragan, BelenTarım, S. Armağan2018-09-192018-09-192018Xiang, M., Rossi, R., Martin-Barragan, B., Tarım, S.A. (2018). Computing non-stationary (s, S) policies using mixed integer linear programming. European Journal of Operational Research, 271(2), 490-500. http://dx.doi.org/10.1016/j.ejor.2018.05.0300377-2217http://hdl.handle.net/20.500.12416/1740This 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.eninfo:eu-repo/semantics/closedAccessInventory(S,S) PolicyStochastic Lot-SizingMixed Integer ProgrammingBinary SearchArticle271249050010.1016/j.ejor.2018.05.030