A charging system is a fundamental requirement for the efficient operation of electric vehicles (EVs) as their usage increases. In light of this, this study examines the most effective approach to the planning of EV battery swapping and charging systems. The optimal locations for EV charging and battery swapping infrastructure in a planned city are determined by solving mixed-integer linear programming problems using advanced optimization techniques, such as Gurobi and Pyomo, in order to minimize the total cost of their seamless operation. Users’ travel time, distance to the nearest station, and the necessity to charge and exchange batteries are all addressed by optimizing service coverage. Additionally, mixed integer linear programming with linear constraints is employed to optimize the geographical coverage, capacity, and range of each station. The decision models guarantee that the majority of users have access to all stations and that there is a balance between charging and battery swapping stations to meet the demand. Furthermore, the model results suggest that urban areas with high population density and traffic congestion require large-scale charging network systems. These observations have the potential to facilitate the effective development and implementation of electric vehicle (EV) charging networks, thereby enhancing user convenience and promoting the growth of electric mobility.