Sustainable and data-driven airport operations: Optimisation models and machine learning approaches

The aerospace industry annually provides transport for billions of passengers along trillions of kilometers. The industry is continuously aiming to provide these services in a more efficient and sustainable way. One possibility is to consider improving airside airport operations, both current types and those expected in the near future....

Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting...

An integrated approach for efficient and resilient airport management