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, Nguyen Binh Duong
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
Subjects:
airport slot scheduling
Reinforcement Learning
strategic
Artificial Intelligence and Robotics
Operations Research, Systems Engineering and Industrial Engineering
Transportation
Online Access:https://ink.library.smu.edu.sg/sis_research/9268
https://ink.library.smu.edu.sg/context/sis_research/article/10268/viewcontent/RL_AirportSlot_CAI_2024_av.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/9268
https://ink.library.smu.edu.sg/context/sis_research/article/10268/viewcontent/RL_AirportSlot_CAI_2024_av.pdf

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