The aeronautical industry is expanding after a period of economic turmoil. For this reason, a growing number of airports are facing capacity problems that can sometimes only be resolved by expanding infrastructure, with the inherent risks that such decisions create. In order to deal with uncertainty at different levels, it is necessary to have relevant tools during an expansion project or during the planning phases of new infrastructure. This article presents a methodology that combines simulation approaches with different description levels that complement each other when applied to the development of a new airport. The methodology is illustrated with an example that uses two models for an expansion project of an airport in The Netherlands. One model focuses on the operation of the airport from a high-level position, while the second focuses on other technical aspects of the operation that challenge the feasibility of the proposed configuration of the apron. The results show that by applying the methodology, analytical power is enhanced and the risk of making the wrong decisions is reduced. We identified the limitations that the future facility will have and the impact of the physical characteristics of the traffic that will operate in the airport. The methodology can be used for tackling different problems and studying particular performance indicators to help decision-makers take more informed decisions.
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.
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