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A system for automated mission planning is presented with a view to operate unmanned aerial vehicles (UAVs) in the National Airspace System (NAS). This paper describes methods for modelling decision variables, for enroute flight planning under visual flight rules (VFR). For demonstration purposes, the task of delivering a medical package to a remote location was chosen. Decision variables include fuel consumption, flight time, wind and weather conditions, terrain elevation, airspace classification and the flight trajectories of other aircraft. The decision variables are transformed, using a multi-criteria decision making (MCDM) cost function, into a single cost value for a grid-based search algorithm (e.g. A*). It is shown that the proposed system provides a means for fast, autonomous generation of near-optimal flight plans, which in turn are a key enabler in the operation of UAVs in the NAS.