Exploiting spatio-temporal partial separability of large-scale airspaces

Abstract

This paper addresses large-scale flight planning via a divide-and-conquer technique that exploits the partial separability feature of the problem. 4D-interaction between flights is used to cluster the flights, and these clusters are then exploited to improve the optimization process. Preliminary computational experiments on the French airspace demonstrate the natural separability of air traffic and yield promising computational improvement for flight planning thanks to the clustering.