CONICET | Buscador de Institutos y Recursos Humanos

This paper studies the network design for a multi-product, multi-echelon and multi-period closed-loop supply chain (CLSC) accounting for decisions on the products to produce (new and remanufactured) and associated raw materials (new and recovered) so as to maximize the CLSC profit. Demands are classified in two types: first and second markets. While the first market is associated with clients that must be satisfied with new products, second market is connected with customers that are interested in buying recycled products in good working condition at low prices. The general network structure includes raw material suppliers, factories, distribution centers, customer demands, recovery centers, recycle centers, final disposal locations and re-distribution centers. Uncertain raw material supplies and customer demands are considered. In addition, risk management related with critical uncertain parameters is performed. As result a two-stage stochastic linear programming approach is developed to investigate possible network improvements by using risk management in the addressed problems. With the objective of achieving risk averse solutions, a multi-objective function based on the expected values and the conditional value at risk (CVaR) concept is applied to both revenues and costs. Thus, the formulation aims to find solutions with high economical and environmental benefits through the CLSC in a context with variable conditions. Environmental aspects are addressed by modeling the CO2 network emissions. The effectiveness of the proposed two-stage stochastic formulation is shown using a realistic case study from a European consumer goods company. The advantages of using the approach considering the variability of the solutions are compared with the features of the results obtained considering a risk neutral performance measure.