Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

Abstract

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.

Original document

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• http://resolver.tudelft.nl/uuid:dc735bd9-3365-456e-969a-0cf5b24aff28

• https://doi.org/10.1016/j.jairtraman.2019.101737

• http://resolver.tudelft.nl/uuid:dc735bd9-3365-456e-969a-0cf5b24aff28,

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• https://www.sciencedirect.com/science/article/pii/S0969699719302303,

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https://academic.microsoft.com/#/detail/2987643707