A stochastic closed-loop supply chain network design problem with multiple recovery options. (April 2018) - Jerbia, Rim; Kchaou Boujelben, Mouna; Sehli, Mohamed Amine; Jemai, Zied
Highlights: We study a closed-loop supply chain network design problem with multiple recovery options. We investigate the impact of variations of the input parameters on profit and network structure. We develop a 2-stage stochastic program with uncertain return rates, costs and return quality. We show that higher penalties lead to a higher value of the stochastic model. Abstract: In this paper, a closed-loop supply chain network design problem with multiple recovery options is studied. First, the deterministic problem is formulated as a Mixed Integer Linear Program (MILP). A sensitivity analysis is carried out in order to investigate the impact of variations of the main input parameters such as customer return rates, revenues, costs as well as the proportions of returns assigned to each recovery option, on the network structure and the company profit. Then, a stochastic version of the model is developed to account for the high uncertainties faced by companies. A scenario-based approach is used to model the uncertainties of return rates, revenues, costs and the quality of returns. The computational results show that the solution of the stochastic problem is stable over different replications and that the benefit from using stochastic modeling increases when the penalty over non collected returns increases.