Four- and Three-Dimensional Aircraft Reference Trajectory Optimization Inspired by Ant Colony Optimization

Abstract

A methodology of aircraft reference trajectory optimization inspired by the ant colony optimization is used in this paper to find the most efficient trajectory in terms of fuel burn and flight cost during the cruise phase. Weather conditions are taken into account in computing the most economical trajectory. The algorithm is designed in two consecutive stages. First, the reference trajectory is optimized in three dimensions. Then, the most economical combination of Mach numbers that fulfills the required time of arrival constraint over that three-dimensional trajectory is found, creating a four-dimensional reference trajectory. Different simulation tests consisted of trajectories following a fixed altitude geodesic trajectory, as well as of real as-flown flights. Simulations revealed that the ant colony algorithm was able to find the most efficient trajectory and the flight cost was 6.82% more economical than the geodesic reference trajectory. Moreover, tests showed that the ant colony algorithm was able to find a four-dimensional trajectory close to the real flight plan trajectory, providing an optimization average of 0.91%. Studies showed that making a three-dimensional trajectory fulfilling the required time of arrival constraint led to an important loss of 2.4% of optimization due to the Mach number changes.