Transactions of Nanjing University of Aeronautics & Astronautics
Bi-level Programming Model for Joint Scheduling of Arrival and Departure Flights Based on Traffic Scenario
- Article
- Figures
- Metrics
- Preview PDF
- Reference
- Related
- Cited by
- Materials
Abstract:
In order to meet the needs of collaborative decision making， considering the different demands of air traffic control units， airlines， airports and passengers in various traffic scenarios， the joint scheduling problem of arrival and departure flights is studied systematically. According to the matching degree of capacity and flow， it is determined that the traffic state of arrival / departure operation in a certain period is peak or off-peak. The demands of all parties in each traffic state are analyzed， and the mathematical models of arrival / departure flight scheduling in each traffic state are established. Aiming at the four kinds of joint operation traffic scenarios of arrival and departure， the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established， respectively， and the elitism genetic algorithm is designed to solve the models. The results show that： Compared with the first-come-first-served method， in the scenarios of arrival peak & departure off-peak and arrival peak & departure peak， the departure flight equilibrium satisfaction is improved， and the runway occupation time of departure flight flow is reduced by 38.8%. In the scenarios of arrival off-peak & departure off-peak and departure peak & arrival off-peak， the arrival flight equilibrium delay time is significantly reduced， the departure flight equilibrium satisfaction is improved by 77.6%， and the runway occupation time of departure flight flow is reduced by 46.6%. Compared with other four kinds of strategies， the optimal scheduling method can better balance fairness and efficiency， so the scheduling results are more reasonable.
Keywords:
Project Supported:
This work was supported by Nanjing University of Aeronautics and Astronautics Graduate Innovation Base （Laboratory） Open Fund （No. kfjj20200717）.
Clc Number:
V355.2
CHINA AERO-SCIENCES
Mobile website
