The current study presents a methodology for analysing and identifying the limitations in capacity of an airport, the methodology has been implemented in the case of Mexico City Airport which is a congested airport in Mexico. The methodology allows identifying what room is left for absorbing more traffic and what options are available while a new infrastructure is in place. The methodology revealed, that there is still room for absorbing more traffic under certain conditions and starting from that, actions can be taken in order to increase the capacity or reducing congestion in the airport.
Airports and surrounding airspaces are limited in terms of capacity and represent the major bottleneck in the air traffic management system. This paper proposes a two level model to tackle the integrated optimization problem of arrival, departure, and surface operations. The macroscopic level considers the terminal airspace management for arrivals and departures and airport capacity management, while the microscopic level optimizes surface operations and departure runway scheduling. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on real-world case studies of Paris Charles De-Gaulle airport, show the benefits of this integrated approach.
