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).
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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).
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Airports represent the major bottleneck in the air traffic management system with increasing traffic density. Enhanced levels of automation and coordination of surface operations are imperative to reduce congestion and to improve efficiency. This paper addresses the problem of comparing different control strategies on the airport surface to investigate their impacts and benefits. We propose an optimization approach to solve in a unified manner the coordinated surface operations problem on network models of an actual hub airport. Controlled pushback time, taxi reroutes and controlled holding time (waiting time at runway threshold for departures and time spent in runway crossing queues for arrivals) are considered as decisions to optimize the ground movement problem. Three major aspects are discussed:1) benefits of incorporating taxi reroutes on the airport performance metrics; 2) priority of arrivals and departures in runway crossings; 3) tradeoffs between controlled pushback and controlled holding time for departures. A preliminary study case is conducted in a model based on operations of Paris Charles De-Gaulle airport under the most frequently used configuration. Airport is modeled using a node-link network structure. Alternate taxi routes are constructed based on surface surveillance records with respect to current procedural factors. A representative peak-hour traffic scenario is generated using historical data. The effectiveness of the proposed optimization methods is investigated.
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Client: European Institute of Innovation and Technology (EIT) The European Institute of Innovation & Technology, a body of the European Union founded to increase European sustainable growth and competitiveness, has set up a number of Knowledge and Innovation Communities (KIC). One of these Communities is on climate change (Climate-KIC). In 2013, Climate-KIC in the Netherlands approved funding for the IMPACT project (IMPlementation & Adoption of Carbon footprint in Tourism travel packages). This ‘pathfinder’ project aimed to assess the viability of and market for a comprehensive carbon calculator. Such a calculator would enable enterprises in the wider travel industry to determine the carbon dioxide emissions, the main cause for climate change, of tourism products and include ‘carbon management’ in their overall policy and strategy. It is generally expected the cost for fuel and carbon will significantly rise in the near en medium future. The calculator will not only cover flights, but also other transport modes, local tourism activities and accommodations. When this pathfinder project finds interest for carbon management within the sector, we aim to start a much larger follow-up project that will deliver the calculator and tools. The IMPACT project was coordinated by the research institute Alterra Wagenigen UR, the Netherlands. Partners were: - Schiphol Airport Group, Amsterdam, The Netherlands- Technical University Berlin, Germany- TEC Conseil, Marseille, France- TUI Netherlands, Rijswijk, The Netherlands- NHTV Breda University for Applied Sciences, The NetherlandsThe project ran from September 2013 to February 2014.
