A stochastic reverse logistics production routing model with emissions control policy selection

Abstract

Carbon emission control policies have emerged in response to the growing global concerns of environmental problems. These regulations should be considered when operational decisions on production, inventory, and routing are being made as emission costs are incurred. In this study, we introduce a reverse logistics supply chain model with remanufacturing and simultaneous pickup and delivery. The problem considers different carbon emission control policies with heterogeneous transportation fleets and allows for lost sales. The aim is to select the optimal carbon control policy with optimal production, inventory, and delivery quantities. The proposed model is formulated as both a deterministic and a two-stage stochastic mixed-integer programming problem. The proposed formulations are demonstrated through two case studies, a simulated reverse logistics supply chain and an actual home appliances production supply chain with remanufacturing options. Sensitivity analyses are conducted to test for the effect of different parameters on the optimal solution. Results indicate that the carbon policy selected has significant effect on the supply chain performance with carbon price being the most significant parameter.