In China, a significant amount of activity is focused on electric vehicles (EV) in recent years. Propelled by the national government, electric buses powered by installed lithium-ion batteries are operating on some metropolitan streets of China. With the drawbacks of short range and long recharge time, the technical features and operating characteristics of battery electric buses and conventional diesel vehicles are different. These differences lead to great changes of the vehicle scheduling method. It is necessary to learn more about the specific scheduling method of electric buses to update traditional bus operation, management rules and scheduling methods. This paper proposes a study to establish a single depot vehicle scheduling model (SDVS) with specific constraints concerning the operation features of electric buses to solve the electric vehicle scheduling problem. Two independent objective functions of minimizing the capital investment for the electric fleet and the total charging demand in stations are involved in the model. To solve the problem, a modified multi-objective optimization method adopting the basic idea of Non-dominated Sorting Genetic Algorithm (NSGA- II) is established. This analysis is performed by solving the scheduling problem for the electric bus demonstration project to be undertaken in Shanghai. Results are reported and verify the practicability of the method proposed in this paper. These findings were valuable to assist the electric bus operation and EV applications.