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
The aeronautical traffic capacity is approaching its limits. This is especially true for airports where airports are constrained to resources such as runways. Consequences of full capacity traffic can be translated to delays and safety issues such as higher collisions risks. One important part of traffic are points where traffic is routed, such as transfer of flights to different ANSPs, sector changes, and merging to meter fixes for landing. There are cases where some entry points to sections are close to maximum capacity, while other entry points to the same section have more capacity. Within the framework of FF-ICE, this paper presents the operational idea of Tactical Demand Tailoring, which consists of balancing traffic by re-routing traffic hours before the arrival of aircraft to a given congested section. This paper proposes the conditions that must be met for TDT to be operationally feasible, and it discusses the potential benefits to increase capacity at overloaded parts of the airspace. Results showed that flights exist under the current flight conditions that can be re-routed to increase capacity. On average, these re-routes result in an approximate 1.9% increase in flight track length. Furthermore, a real-world case study conducted at the Terminal Manoeuvring Area of Schiphol Airport demonstrates that the implementation of Tactical Demand Tailoring effectively mitigates delays.
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.
