Reinforcement learning for strategic airport slot scheduling: analysis of state observations and reward designs

Reinforcement learning for strategic airport slot scheduling: analysis of state observations and reward designs

Due to the NP-hard nature, the strategic airport slot scheduling problem is calling for exploring sub-optimal approaches, such as heuristics and learning-based approaches. Moreover, the continuous increase in air traffic demand requires approaches that can work well in new scenarios. While heuristic...

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Bibliographic Details
Main Authors: Nguyen-Duy, Anh, Pham, Duc-Thinh, Lye, Jian-Yi, Ta, Duong
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference Paper
Language:English
Published: 2025
Subjects:
Computer and Information Science
Other
Reinforcement learning
Airport slot scheduling
Strategic
Online Access:https://hdl.handle.net/10356/182321

Internet

https://hdl.handle.net/10356/182321

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