With the rapid evolution of modern information technologies, various advanced logistics distribution modes and strategies have been put forward in the market. All sectors of society, including the government, have begun to focus on energy issues. How to realize an ideal supply-demand matching of logistics resources is one of the common issues and objectives. To facilitate the development of this platform for both academic researchers and industrial practitioners, a green urban closed-loop logistics distribution network model is proposed in this paper by using the supply and demand data of a logistics service consumer to obtain the optimized solution that minimizes the emissions of greenhouse gases and the overall operational cost. This study aims to assist enterprises to effectively reduce carbon emissions in the current logistics distribution process. This paper uses a case study to validate the feasibility and practicality of the proposed green logistics distribution model to help end-users optimize their daily operations. The results show that there is a negative correlation between the cost and carbon emissions under the shortest distribution routes. However, this negative correlation is not absolute, for instance, certain changes in distribution cost may lead to positive correlation between the cost and carbon emissions. The multi-objective Pareto optimization results also show that the combination of vehicles, including electric vehicles and fuel vehicles, is able to effectively achieve a win-win scenario including carbon emissions and distribution costs, which could be ideal for enterprises. Furthermore, the proposed model could also provide guiding significance for enterprises to achieve low carbon distribution and for governments to promote a low carbon agenda in the urban logistics network distribution system.