COVID-19 arrived in the world suddenly and unexpectedly. It caused major disruptions at economical, operational and other levels. In the case of flight traffic, the operations were reduced to 10% of their original levels. The question after COVID-19 is how to restart the operations and how to keep the balance between safety and capacity. In this paper we present an analysis using simulation techniques for understanding the impact in a security area of an important airport in Latin America; the airport of Mexico City. The results allow to illustrate the potential congestion given by the implemented covid-19 restriction, even when the traffic recovers only by 25% of the pre-covid-19 traffic. The congestion can be mitigated by applying some layout changes (snake queue vs parallel queue) and when more capacity is added to the system (extra security line). The results will raise situational awareness for airport stakeholders when implementing the actions suggested by different international institutions like WHO, IATA or ICAO.
DOCUMENT
Modern airport management is challenged by the task of operating aircraft parking positions most efficiently while complying with environmental policies, restrictions, schedule disruptions, and capacity limitations. This study proposes a novel framework for the stand allocation problem that uses a divide-and-conquer approach in combination with Bayesian modelling, simulation, and optimisation to produce less-pollutant solutions under realistic conditions. The framework presents three innovative aspects. First, inputs from the stochastic analysis module are used in a multivariate optimisation for generating variability-robust solutions. Second, a combination of optimisation and simulation is used to finely explore the impact of realistic uncertainty uncaptured by the framework. Lastly, the framework considers the role of human beings as the final control of operational conditions. A case study is presented as a proof of concept and demonstrates results achievable and benefits of the framework proposed. The experimental results demonstrate that the framework generates less-pollutant solutions under realistic conditions.
DOCUMENT
