The United Nations Humanitarian Air Service (UNHAS) currently performs their flight planning by hand, resulting in possibly non optimal routing with little decision support. Research has mainly focused on commercial applications, leaving humanitarian applications underexposed. This study aims at improving the efficiency and effectiveness of flight routing and scheduling in a humanitarian setting by creating a linear programming model. A novel, airport-based, formulation of the vehicle routing problem is presented. Based on this formulation a model is created that also incorporated the monthly minimum guaranteed flight hours per aircraft. The results of this model are compared to human flight planners and a reference model. When considering day-to-day optimization, the model realized cost savings of 4.6% till 10.5% with respect to the human flight planners and 1.8% compared to a reference model. When considering the minimum guaranteed hours, the model obtained solutions that were 4% cheaper compared to the daily optimization mode and 1.6% compared to the human flight planner. Furthermore, analyses were performed that offer insight in the effect of the contract structure on the operational costs.