Mexico City airport is located close to the center ofthe city and is Mexico’s busiest airport which is consideredcongested. One of the consequences of airport congestion areflight delays which in turn decrease costumer’s satisfaction. Airtraffic control has been using a ground delay program as a toolfor alleviating the congestion problems, particularly in the mostcongested slots of the airport. This paper uses a model-basedapproach for analyzing the effectiveness of the ground delayprogram and rules. The results show that however the rulesapplied seem efficient, there is still room for improvement inorder to make the traffic management more efficient.
MULTIFILE
The relentless growth in Mexico City’s aviation traffic has inevitably strained capacity development of its airport, raising thedilemma between the possible solutions. In the present study, Mexico’s Multi-Airport System is subjected to analysis by meansof multi-model simulation, focusing on the capacity-demand problem of the system. The methodology combines phases ofmodelling, data collection, simulation, experimental design, and analysis. Drawing a distinction from previous works involvingtwo-airport systems. It also explores the challenges raised by the Covid-19 pandemic in Mexico City airport operations, with adiscrete-event simulation model of a multi-airport system composed by three airports (MEX, TLC, and the new airport NLU).The study is including the latest data of flights, infrastructures, and layout collected in 2021. Therefore, the paper aims toanswer to the question of whether the system will be able to cope with the expected demand in a short-, medium-, and longtermby simulating three future scenarios based on aviation forecasts. The study reveals potential limitations of the system astime evolves and the feasibility of a joint operation to absorb the demand in such a big region like Mexico City.
