Slot Scheduling in Air Transportation

Following Alexandre Jacquillat’s talk at the STOR-i Annual Conference 2020 on Analytics for Operations, Scheduling and Pricing in Air Transportation, I was inspired to investigate this topic some more. I was particularly interested in the concept of slot scheduling to better use scarce airport capacity in order to improve the efficiency of the air transportation system. After reading some of the relevant literature and attending a talk by Konstantinos G. Zografos, I decided to write my first STOR-i research report on models proposed to deal with slot allocation inefficiencies. I have detailed the one-page summary of my report below:

Summary of Research Report

The slot scheduling problem has recently received a great deal of consideration in the literature due its size and complexity. As demand for air transportation rises but opportunities for the expansion of infrastructure remain limited, demand management measures are fundamental to help balance supply and demand. Supply side solutions, through airport capacity expansion or enhancement, are capital intensive and require a long term horizon for implementation. Such operations are also often subject to physical or political constraints. Instead, demand management is recognised as the principal instrument to deal with delays in air transport since such solutions are immediate and easily implementable. Slot scheduling is a method of managing demand through best allocating scarce airport resources.

Prior to the summer or winter scheduling season, airlines request slots at an airport; a slot allows them to use all of the infrastructure necessary for landing and take-off. For airports who are designated as `coordinated’, due to supply-demand imbalances, a coordinator is responsible for allocating slots. Currently slot schedules exhibit large deviations from requested slot times. Airport capacity is usually expressed in terms of the number of available slots and the demand for these slots often exceeds capacity, but this capacity is rarely used optimally. Slot scheduling models aim to best use capacity so that all airlines are allocated slots as close to their requests as possible, subsequently slots are used more efficiently and delays are minimised. There is large room for improvement in the current slot allocation process.

The first mathematical model to be compliant with scheduling regulations was proposed in 2012. This model aims to minimise the distance between requested and allocated slot times subject to an artificial measure of capacity and turnaround time constraints, at a single airport. This ensures capacity is not exceeded, so delays are minimised, and allows the aircraft sufficient time on the ground to prepare for the next flight. Using this simple formulation, the resulting schedule demonstrates large improvements on current procedures. Following from this, other models have been developed to also incorporate fairness and accessibility restrictions. These encourage flights to remotely located airports and aim to ensure no airline suffers greater displacement from their requested slots. This means all airlines are treated equally and all airports, regardless of size, are accessible. Other models aim to minimise similar objectives, but consider a network of airports. This means that dependencies between airports are accounted for in order to avoid the multiplier effect of delays once one flight is interrupted. Considering a network of airports creates a larger and more complex problem, but this helps to formulate a more realistic representation of the situation at hand.

This report reviews the current slot allocation procedure, detailing each stage necessary to formulate a slot schedule. Additionally, we discuss different allocation models in the surrounding literature, at the single and network level, and use computational results to compare them to the existing methods, as well as one another. Finally, we aim to identify any gaps in the research that present interesting ideas for future investigation.

Further Reading

The models I focussed on for this report are taken from the following papers:

• Zografos, K. G., Salouras, Y., and Madas, M. A. (2012). Dealing with the efficient allocation of scarce resources at congested airports. Transportation Research Part C: Emerging Technologies, 21(1):244- 256.

• Zografos, K. and Jiang, Y. (2016). Modelling and solving the airport slot scheduling problem with efficiency, fairness, and accessibility considerations.

• Castelli, L., Pellegrini, P., Pesenti, R., et al. (2011). Airport slot allocation in europe: economic efficiency and fairness. International journal of revenue management, 6(1-2):28-44.

• Corolli, L., Lulli, G., and Ntaimo, L. (2014). The time slot allocation problem under uncertain capacity. Transportation Research Part C: Emerging Technologies, 46:16-29.