Yutian Pang, PhD

Yutian Pang, PhD

Postdoctoral Fellow, Aerospace Engineering & Engineering Mechanics

Machine Learning-Enhanced Aircraft Landing Scheduling under Uncertainties

Published in Transportation Research Part C: Emerging Technologies, 2024 · arXiv

Representative figure for this publication
Overview of the machine learning enhanced optimization model for aircraft landing scheduling: flight data handling from the Sherlock Data Warehouse, quantile gradient boosting for landing time distributions, sequencing as a traveling salesman problem with time windows, and the optimized landing sequence against the first come first served baseline.

Blends machine-learned arrival-time distributions with optimization to schedule aircraft landings that stay efficient under uncertainty.

Representative publication of this research line.

Recommended citation 

@article{pang2024machine,
  title = {Machine Learning-Enhanced Aircraft Landing Scheduling under Uncertainties},
  author = {Pang, Y. and Zhao, P. and Hu, J. and Liu, Y.},
  journal = {Transportation Research Part C: Emerging Technologies},
  volume = {158},
  pages = {104444},
  year = {2024},
  eprint = {2311.16030},
  archivePrefix = {arXiv},
  primaryClass = {cs.AI},
  url = {https://arxiv.org/abs/2311.16030}
}