This research aims to find relevant evidence on whether there is a link between air capacity management (ACM) optimization and airline operations, also considering the airline business model perspective. The selected research strategy includes a case study based on Paris Charles de Gaulle Airport to measure the impact of ACM optimization variables on airline operations. For the analysis we use historical data which allows us to evaluate to what extent the new schedule obtained from the optimized scenario disrupts airline planned operations. The results of this study indicate that ACM optimization has a substantial impact on airline operations. Moreover, the airlines were categorized according to their business model, so that the results of this study revealed which category was the most affected. In detail, this study revealed that, on the one hand, Full-Service Cost Carriers (FSCCs) were the most impacted and the presented ACM optimization variables had a severe impact on slot allocation (approximately 50% of slots lost), fuel burn accounted as extra flight time in the airspace (approximately 12 min per aircraft) and disrupted operations (approximately between 31% and 39% of the preferred assigned runways were changed). On the other hand, the comparison shows that the implementation of an optimization model for managing the airport capacity, leads to a more balanced usage of runways and saves between 7% and 8% of taxi time (which decreases fuel emission).
MULTIFILE
Airport operations are undergoing significant change, having to meet pandemic requirements in addition to intrinsic security requirements. Although air traffic has declined massively, airports are still the critical hubs of the air transport network. The new restrictions due to the COVID-19 pandemic pose new challenges for airport operators in redesigning airport terminals and managing passenger flows. To evaluate the impact of COVID-19 restrictions, we implement a reference airport environment. In this Airport in the Lab environment we will demonstrate the operational consequences derived from the new operational requirements. In addition, countermeasures to mitigate any negative impacts of these changes are tested. The results highlight emerging issues that the airport will most likely face and possible solutions. Finally, we could apply the findings and lessons learned from our testing at our reference airport to a real airport.
