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Multi-Objective Airport Slot Scheduling Incorporating Operational Delays and Multi-Stakeholder Preferences

Research output: Working paper

Publication date16/02/2022
Number of pages41
<mark>Original language</mark>English

Publication series



Airport Slot Allocation (ASA) is a multi-objective, multi-stakeholder decision process that aims to maximise airport capacity utilisation and mitigate delays. Studies on the ASA problem proposed multi-objective formulations that generate the efficient frontier representing the trade-offs among the considered optimisation objectives. However, all formulations proposed so far in the literature have only considered objectives associated with the slot scheduling process per se and have neglected the implications of the alternative schedules, represented by the generated efficient frontier, on the operational delays, i.e., the delays that will be encountered when a selected airport schedule will be implemented. Failure to consider operational delays during the ASA process may lead to schedules with adverse operational consequences for all stakeholders involved in the ASA process. Furthermore, the ASA literature currently lacks an integrated methodology that will incorporate, in a systematic way, the preferences of all ASA stakeholders/experts in selecting the most preferable airport schedule. In addition, in the current literature, there are no empirical studies aiming to demonstrate how the elicitation of the stakeholders/experts’ preferences can be used to select the most preferable schedule. The new ASA approach introduced in this paper addresses the above literature gaps by considering two important problem attributes previously untapped, namely the consideration of operational delays and the elicitation and integration of multi-stakeholder preferences in ASA decision-making. Our approach guarantees the generation of all non-dominated schedules and reduces decision-making complexity by selecting representative schedules. Each schedule is assessed based on the preferences of all pertinent stakeholder groups concerning both its operational and strategic performance. The proposed solution methodology is tested using empirical preference data that are obtained from experts coming from all stake-holding groups of the ASA process. Computational results suggest that the proposed methodology may provide crucial decision-support and catalyse the determination of the most preferable airport slot scheduling solution (or solutions) and its implications on expected delays. Our approach results in schedules with maximum delays that are consistently below 26.5 minutes for all preference scenarios.