In order to reduce the carbon emission of vehicles during the process of logistics distribution, on the perspective of green environmental protection, a Green Vehicle Routing Problem (GVRP) of logistics distribution vehicles with multi-type vehicles considering traffic congestion areas was analyzed. Firstly, the effect of multi-type vehicles and different traffic congestion situations on the vehicle route planning was investigated. Secondly, the metric function of carbon emission rate was introduced on the basis of vehicle speed and load. Thirdly, a dual-objective green vehicle routing model with minimizing the vehicle management cost as well as the fuel consumption and carbon emission cost as optimization objects was established. Finally, a hybrid differential evolution algorithm combined with simulated annealing algorithm was designed to solve the problem. Simulation results verify that the model and algorithm can effectively avoid the congestion areas. Compared to the simulation results only using 4 t vehicles for distribution, the proposed model has the total cost reduced by 1.5%, and the fuel consumption and carbon emission cost decreased by 4.3%. Compared the model with optimization objective of shortest driving distance, the proposed model has the total distribution cost decreased by 8.1%, demonstrating that the model can improve the economic benefits of logistics enterprises and promote the energy saving and emission reduction. At the same time, compared with the basic differential algorithm, the hybrid differential evolution algorithm with simulated annealing algorithm can reduce the total transportation cost by 3% to 6%； compared with the genetic algorithm, the proposed algorithm has more obvious optimization effect, and has the total transportation cost reduced by 4% to 11%, proving the superiority of the algorithm. In summary, the proposed model and algorithm can provide effective advices for the urban distribution routing decision of logistics enterprises.