Design of a Third party Reverse Logistics Network under a Carbon Tax Scheme
Reverse logistics network involves significant inherent uncertainties, which cannot be completely characterized because of a lack of adequate historical data. In this study, a multi product and multi period interval programming model was developed on the basis of partial information to design an effective reverse logistics network. In addition, the trade off between economic benefits and the environmental burdens from carbon emissions was analyzed by considering the effect of a carbon tax scheme on the reverse logistics network design. Through an improved and modified interval linear programming method, the optimal interval solution was obtained with LINGO. Finally, numerical simulations were conducted to explore the effectiveness of the model and the effect of the carbon tax scheme. Results show that the optimal solution of the reverse logistics network design is robust. The effect of the carbon tax scheme is trivial when the carbon tax is low and significant when the carbon tax is high. As carbon tax gradually increases, carbon emissions effectively decrease, but sharply declines the total profit sharply declines. The findings indicate that the proposed model can effectively solve the reverse logistics network design with partial information under a carbon tax scheme.