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A Bi-objective Efficiency-Fairness Model for Scheduling Slots at Congested Airports

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>1/05/2019
<mark>Journal</mark>Transportation Research Part C: Emerging Technologies
Volume102
Number of pages15
Pages (from-to)336-350
Publication statusPublished
Early online date22/03/19
Original languageEnglish

Abstract

Slot scheduling has emerged as an issue of major concern at congested airports. A commonly used metric for assessing airport slot scheduling efficiency is total schedule displacement. In addition to schedule efficiency, fairness has also been identified as another important slot scheduling criterion. However, the literature currently does not provide sufficient modelling capabilities for investigating the single airport slot scheduling efficiency-fairness trade-off. The objective of this paper is to develop and solve a novel airport slot scheduling model which considers simultaneously slot scheduling efficiency and fairness objectives. We introduce a fairness metric for slot scheduling and formulate the airport slot scheduling problem as a bi-objective optimization model which considers fairness and efficiency simultaneously. We use an integrated solution framework that combines the ε-constraint method and a row generation algorithm to solve the proposed bi-objective model. We investigate the slot scheduling efficiency-fairness trade-off under the following two slot scheduling regimes: (i) a regime that considers historical slot usage rights (hierarchical), and (ii) a regime that does not consider historical slot usage rights (non-hierarchical). The proposed model generates the efficient frontiers describing the slot scheduling efficiency-fairness trade-off for both slot scheduling regimes. The results of the model are presented at the aggregate (airport-wide) and disaggregate (individual) airline level providing information that enhances the transparency of slot scheduling decisions. The efficient frontiers produced by the proposed model can facilitate discussions among different stakeholders in making slot scheduling decisions.