An Extended Mixed-Integer Programming Formulation and Dynamic Cut Generation Approach for the Stochastic Lot-Sizing Problem

• DOI: 10.1287/ijoc.2017.0792
• Publication Date: 2018-09-21T15:49:58Z
• Authors: Huseyin Tunc; Onur A. Kilic; S. Armagan Tarim; Roberto Rossi
• Keywords: static-dynamic uncertainty; DEMAND; extended formulation; COST; 0211 other engineering and technologies; POLICIES; 02 engineering and technology; stochastic lot sizing; dynamic cut generation; SERVICE-LEVEL CONSTRAINTS; MODEL; UNCERTAINTY STRATEGY; ALGORITHM; INVENTORY SYSTEMS; APPROXIMATION

We present an extended mixed-integer programming formulation of the stochastic lot-sizing problem for static-dynamic uncertainty strategy. The proposed is significantly more time efficient as compared to existing formulations in literature and it can handle variants characterized by penalty costs service level constraints, well backorders lost sales. Also, besides being capable working with a predefined piecewise linear approximation cost function—as case earlier formulations—it has functionality finding optimal solution arbitrary precision means novel dynamic cut generation approach. online appendix available at https://doi.org/10.1287/ijoc.2017.0792 .