This paper takes the comprehensive system problem of charging station location and shortest path optimization faced by new energy vehicles in the distribution process as the research object. We hope to obtain a combination optimization method that can further support China’s use of new energy vehicles to complete urban distribution problems. This paper addresses the existing comprehensive challenges related to route selection and site allocation. It takes into account the short transportation mileage and low load capacity of new energy vehicles caused by charging constraints. At the same time, considering the timeliness of modern urban distribution, time window constraints and logic constraints are added. Taking the minimum number of charging stations and the minimum transportation cost as the multi-objective problem of combinatorial optimization, the mathematical model is finally established. After transforming the multi-objective problem into a single-objective problem, the genetic algorithm the genetic algorithm is used to solve the system problem comprehensively. Finally, an example is used to verify the feasibility and effectiveness of genetic algorithm in solving the new energy vehicle distribution – location path combination optimization problem. It provides theoretical support and development prospects for further promoting urban distribution of new energy vehicles in the future.