Abstract
Airport Slot Allocation (ASA) is a multi-objective, multi-stakeholder decision process that aims to maximise airport capacity utilisation and mitigate delays. Existing ASA studies have considered objectives associated with the slot scheduling process per se without considering 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. Furthermore, one notes the absence of an integrated methodology that incorporates the preferences of all ASA stakeholders/experts in selecting the most preferable airport schedule. This gap becomes more evident when considering the dearth of empirical data with respect to ASA scheduling performance metrics. The ASA framework proposed herein taps the above gaps by considering operational delays and eliciting airport slot schedules through the integration of multi-stakeholder preferences. Computational results using empirical preference data demonstrate the decision-support in determining the most preferable airport slot scheduling solution (or solutions) and its implications on expected delays.
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