Multi-objective Aircraft Trajectory Optimization for Weather Avoidance and Emissions Reduction

During the flight, aircraft produces several pollutant emissions and the amount is deeply related to the atmospheric conditions (especially pressure, humidity, temperature, air density and wind), the aircraft performance and the phase of flight. In this paper an approach, based on Dijkstra algorithm, to calculate optimized trajectory in terms of several emission reduction (multi-objective trajectory optimization) is illustrated and some results, in case of a real flight and real weather conditions, are reported. The emissions to be simultaneously reduced are CO2 (proportional to fuel consumption [1], NOx and noise and the aircraft considered is an A320, DAL1451, in USA, in climb phase. The simultaneous reduction of all these three pollutants is nontrivial as reducing one pollutant can lead to an increase in the others [2]. The optimization of more than one objective sets a problem on how to combine the single objectives in order to find a satisfactory solution. The chosen approach is to combine the different pollutant using a linear combination. The weight to be assigned to each pollutant could vary and lead to different results. In this paper it is proposed the use of the Pareto optimal solution method to determine a set of optimal weights for multi-criteria optimization of pollutant emissions. Key-Words: multi-objective trajectory optimization, Dijkstra, genetic algorithms, weather avoidance, emissions reduction, Pareto, aircraft performance.