Due to the growing demand in air transport, measures need to be taken to reduce the impact of noise and emissions on local communities and the environment. The generic nature of current departure procedures leaves room for improvement in the form of aircraft type dependent departure trajectories. In this study a trajectory optimization model is implemented that uses a multi-objective evolutionary algorithm to optimize departure trajectories for fuel consumption and awakenings from noise. A parameterization technique is applied that reduces the number of optimization parameters by splitting the horizontal and vertical profiles into segments, thereby reducing the complexity of the problem. The model is used to optimize a specific departure trajectory at Schiphol Airport. A 15% reduction in fuel and a 60% decrease in number of awakenings is possible when an aircraft flies a fuel or noise optimal trajectory respectively. An intermediate trajectory provides a trade-off between the two objectives that is still superior to the reference. Medium aircraft can share an optimal trajectory without significant deterioration in performance while this does not apply for heavy aircraft. The achieved fuel savings translate to lower CO2 emissions which contribute to reaching EU climate goals, while the reduction in number of awakenings results in fewer restrictions on the maximum number of aircraft movements. Both aspects allow the air transport industry to continue growing in a sustainable manner in the future.