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

• المؤلفون الرئيسيون: Nguyen-Duy, Anh, Pham, Duc-Thinh, Lye, Jian-Yi, TA, Nguyen Binh Duong
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2024
• الموضوعات: airport slot scheduling; Reinforcement Learning; strategic; Artificial Intelligence and Robotics; Operations Research, Systems Engineering and Industrial Engineering; Transportation
• الوصول للمادة أونلاين: 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
• المؤسسة: Singapore Management University

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...