Moving several autonomous aerial vehicles in a shared airspace is a difficult task, and even more for a fleet of fixed-wing aircraft. This problem can arise in several situations, such as formation flight or airport landing. These require maintaining a minimal separation while staying at cruise speed and reaching destination at a given time. This thesis seeks to answer this question by presenting a centralized method based on enumerating different Dubins paths, called Dubins Fleet Path Planner. Given a travel time for the fleet, it builds a set of possible paths for each aircraft. Then, it checks separation between each path pair. This yields coefficients for an Integer Linear Programming problem determining if a fleet-wide conflict-free solution exists. This process is repeated for different travel times sampled with increasing resolution until the user-defined accuracy or maximal runtime is met. It is also shown that the method can take into account a constant uniform wind, and can be adapted to managing airport approaches. The Dubins Fleet Path Planner is first validated using Monte-Carlo simulations for setting up to 20 Uncrewed Aerial Vehicles in formation simultaneously, achieving an 95\% success rate for an average 8-second computation time. Then it is used for a real formation flight using 3 Parrot Disco, and replanning approach traffic at the London Heathrow Airport based on data from the OpenSky network.