[QGK18a] Valid inequalities for solving a stochastic lot-sizing problem with returns

Conférence Internationale avec comité de lecture : ISMP, July 2018, France,
Résumé: We seek to plan production activities on a re-manufacturing system over a multi-period horizon. The system comprises three processes; disassembly, refurbishing and reassembly. Uncertainties are assumed on the quality and quantity of re- turned products, customers demand and production costs. This leads to a multi-echelon stochastic lot-sizing problem with product returs and lost sales minimizing the total ex- pected production costs. We propose a multi-stage stochastic integer programming approach relying on a scenario tree to represent the uncertain information structure, resulting in the formulation of a large-size MILP. New valid tree inequalities are obtained by mixing previously known path inequalities. They are used in a Branch-and-Cut framework to solve the problem. Computational results will illustrate the effectivness of the proposed method. The number of instances solved to optimality is increased by a factor of 1.8 as compared to the use of the commercial solver CPLEX.


@inproceedings {
title="{Valid inequalities for solving a stochastic lot-sizing problem with returns}",
author=" F. Quezada and C. Gicquel and S. Kedad-Sidhoum ",
address=" France",