Smart charging is becoming an important and indispensable asset for electric bus fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric bus fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions.