An optimization approach for airport slot allocation under IATA guidelines

• Published in: Transportation research. Part B: methodological Vol. 112; pp. 132 - 156
• Main Authors: Ribeiro, Nuno Antunes, Jacquillat, Alexandre, Antunes, António Pais, Odoni, Amedeo R., Pita, João P.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.06.2018; Elsevier Science Ltd
• Subjects: Air traffic; Air traffic control; Air transportation; Airlines; Airport capacity; Airport demand management; Airports; Allocations; Computer applications; Demand; Guidelines; IATA guidelines; Integer programming; Multiple objective analysis; Optimization; Priorities; Slot allocation; Traffic capacity; Traffic management; Integer programming; Slot allocation; IATA guidelines; Airport demand management
• ISSN: 0191-2615; 1879-2367
• DOI: 10.1016/j.trb.2018.04.005

•We develop a modeling and computational approach to optimize airport slot allocation.•The Priority-based Slot Allocation Model (PSAM) complies with the IATA guidelines.•Strong formulations yield exact solutions at medium-size airports for a full season.•The PSAM is applied at the Madeira and Porto airports using detailed real-world data.•Results suggest that the PSAM can improve slot allocation outcomes at busy airports. Air traffic demand has grown to exceed available capacity during extended parts of each day at many of the busiest airports worldwide. Absent opportunities for capacity expansion, this may require the use of demand management measures to restore the balance between scheduled traffic and available capacity. The main demand management mechanism in use today is the administrative schedule coordination process operated by the International Air Transport Association (IATA), which is in place at the great majority of busy airports outside the United States. This paper proposes a novel multi-objective Priority-based Slot Allocation Model (PSAM) that optimizes slot allocation, while complying with the complex set of priorities and requirements specified by the IATA guidelines, as well as with the declared capacity constraints at the airports. It presents an efficient computational approach that provides optimal slot allocation solutions at airports significantly larger than has been possible to date. The model is applied to two Portuguese airports, a small one (Madeira) and a mid-size one (Porto) using highly detailed data on airline slot requests and airport capacity constraints. Results suggest that PSAM can improve the efficiency of current practice by providing slot allocations that match better the slot requests of airlines. Equally important, PSAM can also quantify the sensitivity of slot allocation decisions to the various priorities and requirements specified in the IATA guidelines.