Tunc, HuseyinKilic, Onur A.Tarim, S. ArmaganRossi, 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)1091-98561526-5528https://doi.org/10.1287/ijoc.2017.0792Tunc, Huseyin/0000-0001-5508-3702; Kilic, Onur/0000-0003-2136-8157; Rossi, Roberto/0000-0001-7247-1010; Tarim, S. Armagan/0000-0001-5601-3968We 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/openAccessStochastic Lot SizingStatic-Dynamic UncertaintyExtended FormulationDynamic Cut GenerationArticle30349250610.1287/ijoc.2017.07922-s2.0-85055165232WOS:000449096000006Q3Q2