A stochastic reverse logistics production routing model with environmental considerations

Growing global concerns of environmental problems have led to the emergence of policies and regulations to control carbon emissions in the industrial sector. These regulations must be taken into consideration to obtain optimal operational decisions on production, inventory and routing in supply chain network models. In this study, we consider the reverse logistics supply chain model with a remanufacturing option to reduce carbon emissions. We aim at providing optimal production, inventory and delivery quantities along with delivery and pickup routes under a carbon cap-and-trade emissions policy. We provide a mathematical formulation of the problem that considers heterogeneous transportation fleets and allows for lost sales under the cap-and-trade carbon emissions policy. The proposed mathematical model is provided in a deterministic and a two-stage stochastic versions to account for demand uncertainty. Proposed formulations are demonstrated through a simulated reverse logistics supply chain with added sensitivity analysis to test for the effect of modeling parameters on the optimal problem solution. Simulation results indicate that carbon policies have significant effect on the supply chain performance with carbon price as the most significant parameter.