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A decision making framework for incorporating fairness in allocating slots at capacity-constrained airports

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
Article number103039
<mark>Journal publication date</mark>1/05/2021
<mark>Journal</mark>Transportation Research Part C: Emerging Technologies
Volume126
Number of pages19
Publication StatusPublished
Early online date16/03/21
<mark>Original language</mark>English

Abstract

Fairness constitutes an important criterion for allocating scarce resources among self-interested parties. The capacity of congested airports is a scarce resource which is allocated in the form of slots to airlines to operate their flights. Traditionally, the optimisation of slot allocation efficiency has been considered as the primary criterion in making slot allocation decisions at capacity-constrained airports. The efficiency of slot allocation is expressed as a function of displacement, which is defined as the difference between the time requested by the airlines and the time allocated to airlines to operate their flights. Recent research work has considered fairness as an additional slot allocation objective. However, the literature has not adequately addressed the following two key research questions: i) in the presence of alternative fairness measures, which fairness measure should be used to investigate the slot allocation efficiency-fairness trade-off, and how the choice of the efficient frontier describing this trade-off should be made? and ii) given that the choice of the efficient frontier has been made, which slot allocation solution should be selected for implementation, and how this choice should be made? To address these questions, we investigate three inter-airline fairness objectives, and we introduce a decision-making framework to assist decision-makers in identifying the most preferable acceptable slot allocation outcome. The proposed decision-making framework is based on a voting mechanism which incorporates the preferences of stakeholders. We use slot request and capacity data to determine the most preferable slot allocation outcome at a capacity-constrained airport.