Faced with the contradiction between the rapid growth of car ownership and the low recovery rate of end-of-life vehicles, the reverse logistics services led by third-party recycling and dismantling companies for end-of-life vehicles (ELVs) in China are experiencing great challenges under the background of the low-carbon economy. This paper constructs a four-tier reverse logistics network model, which includes ELV sources, collection centers, remanufacturing centers and dismantlers. Meanwhile, this paper also develops a mixed integer linear programming mathematical model and solves the problem using the global optimization software Lingo. The optimization results of a real case in Xi’an prove the validity of the model in both present normal demands and increasing demand situations in the future. The total logistics network and the environmental costs are both reduced, and the utilization rate of the dismantling center is improved. The location and capacity rating strategies in dismantling centers have key effects on the total cost in the logistics network that are far beyond other decision variables. The supply capacity of the key facilities in Xi’an’s ELV recycling network is far greater than the level of demand, causing a serious waste of resources. Hence, the layout model of an industrial park can help to reduce the total cost of the reverse logistics network if the dismantling center has a high utilization rate.