Slot allocation for a multiple-airport system considering airspace capacity and flying time uncertainty
Prior research on slot allocation has focused on a single airport, with little attention paid to the multiple-airport systems (MAS) that consist of at least two major airports. Scheduled flights at different airports may have conflicts regarding shared fixes (i.e., route points) or routes, thus caus...
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| Main Authors: | , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2023
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/8247 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Prior research on slot allocation has focused on a single airport, with little attention paid to the multiple-airport systems (MAS) that consist of at least two major airports. Scheduled flights at different airports may have conflicts regarding shared fixes (i.e., route points) or routes, thus causing airspace congestion and flight delays. Traffic demand at a critical fix depends on both the departure/arrival time of the flights and the flying times between the airport and the fix, whereas flying times exhibit a stochastic nature due to various factors such as air traffic control strategies, aircraft performance, and weather. In this paper, we develop a chance-constrained slot allocation model for an MAS that optimizes slot allocation for multiple airports while considering fix capacity constraints. To capture the uncertainty of flying times, stochastic chance constraints are formulated and a scenario generation method is proposed to solve the model. We apply our model to allocate slots in the MAS of Guangdong-Hong Kong-Macao Greater Bay area. The results show that the schedules generated by the proposed model outperform those from the certainty model and the original schedules. Traffic flow at critical fixes is more robust to various operating scenarios with the cost of a small number of increased slot displacements. Our findings highlight the importance of flying time uncertainty in allocating slot and airspace capacity, and the proposed model provides a useful tool for slot coordinators seeking to effectively manage airport slots in an MAS. |
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