The Chinese government has now published its emission reduction goal of carbon dioxide by 2020 and any industrial player is obliged to take effective initiatives to decrease its carbon footprint. For the city logistics distribution system, as a significant energy-consuming and pollutant-emitting sector, energy saving and emission reduction are very meaningful especially for megacities like Beijing. With rational hypotheses and parameter design, meanwhile considering the deployment of low-carbon resources, a novel carbon tax-constrained city logistics distribution network planning model is proposed. The model is a bilinear non-convex mixed integer programming and is reduced to a pure linear mixed integer programming through proper linearization. To verify the effectiveness of the model, an empirical study is conducted on a city logistics operator in Beijing and the popular commercial optimization suite IBM ILOG CPLEX is adopted for optimization purpose. Through analysis of the optimization results and comparison with traditional optimization models, it is found that the proposed model can help the city logistics distribution operator save up to 9.2% of operational cost during a full service cycle, and meanwhile cut down its carbon dioxide discharge by around 54.5% or 2135 metric tons at most.
