Tunç, HüseyinKılıç, Onur A.Tarım, S. ArmağanRossi, Roberto2020-03-272020-03-272018Tunc, Huseyin; Kilic, Onur A.; Tarim, S. Armagan; et al. "An Extended Mixed-Integer Programming Formulation and Dynamic Cut Generation Approach for the Stochastic Lot-Sizing Problem", Informs Journal On Computing, Vol. 30, No. 3, pp. 492-506, (2018)1091-9856http://hdl.handle.net/20.500.12416/2776We present an extended mixed-integer programming formulation of the stochastic lot-sizing problem for the static-dynamic uncertainty strategy. The proposed formulation is significantly more time efficient as compared to existing formulations in the literature and it can handle variants of the stochastic lot-sizing problem characterized by penalty costs and service level constraints, as well as backorders and lost sales. Also, besides being capable of working with a predefined piecewise linear approximation of the cost function-as is the case in earlier formulations-it has the functionality of finding an optimal cost solution with an arbitrary level of precision by means of a novel dynamic cut generation approach.eninfo:eu-repo/semantics/closedAccessStochastic Lot SizingStatic-Dynamic UncertaintyExtended FormulationDynamic Cut GenerationArticle30349250610.1287/ijoc.2017.0792