Aircraft ground traffic optimisation using a genetic algorithm

Brankica Pesic (1) , Nicolas Durand (2) , Jean-Marc Alliot (3)

1 University of Belgrade [Belgrade]
2 ENAC - Ecole Nationale de l'Aviation Civile
3 DGAC - Direction Générale de l'Aviation Civile

The development of air traffic during the last years, has greatly increased the density of aircraft in the airspace, and congestion on major airports. Indeed, on many airports, the taxi operation of aircraft between parking positions and runways, causes delays. The problem is increased by the development of hubs. In this article, a taxi optimisation tool using a Genetic Algorithm is introduced and tested on Roissy Charles De Gaulle Airport. The tool can help choosing the best taxiways to reduce the time spent from the gate to the runway or the runway to the gate, respecting the separation with other aircraft. It can also help choosing one way taxiways regarding to traffic and wind, and also measuring the impact of opening a new taxiway or closing an existing taxiway. Simulations are presented on a one day traffic at Paris Roissy. Delays are correlated to the traffic density on the airport.

Domaines: Optimisation et contrôle [math.OC]

Brankica Pesic, Nicolas Durand, Jean-Marc Alliot. Aircraft ground traffic optimisation using a genetic algorithm. GECCO 2001, Genetic and Evolutionary Computation Conference, Jul 2001, San Francisco, United States. pp xxxx. ⟨hal-00938003⟩