An extended mixed-integer programming formulation and dynamic cut generation approach for the stochastic lot sizing problem

Dr. Hüseyin Tunç

Abstract

We present an extended MIP 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 pre-defined 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.

Short Bio

Dr. Huseyin Tunc is an assistant professor of operations research at Hacettepe University. Prior to joining Hacettepe university, he worked as a post-doctoral associate at Mississippi State University in USA. Also, he was a visiting scholar at Swiss Federal Intitute of Technology in Lausanne (EPFL). Dr. Huseyin Tunc received his Ph.D. in Industrial and Systems Engineering from Mississippi State University in 2012. He holds M.Sc. in Operations Research and B.Sc. in Management both from Hacettepe University. His research interests are mainly towards the theory and applications of operations research problems under uncertainty particularly focusing on applications in supply chain management, operations management, and inventory management. He has published his research in journals including INFORMS Journal on Computing, European Journal of Operational Research, Operations Research Letters, and OMEGA.

Venue

Wednesday, May 30, 2018 at 2pm