Bi-Level Scheduling for Beijing-Tianjin-Airport Cluster Departures

The rapid growth of air traffic demand and limited airspace resources have made efficient coordination in multi-airport systems a critical challenge. This paper develops a bi-level air–ground collaborative scheduling model for the Beijing-Tianjin-Airport cluster, integrating terminal-area departure sequencing (upper level) with airport surface taxi and pushback scheduling (lower level), where the upper-level model minimizes departure delays, maximizes airport satisfaction, and reduces fairness deviation, while the lower-level model optimizes taxi routing and pushback timing. To solve the model, NSGA-II is applied to the upper-level sequencing problem and a Genetic-Simulated Annealing algorithm is used for surface scheduling. Empirical evaluation using operational data from Beijing Capital, Beijing Daxing, and Tianjin Binhai airports shows that the proposed approach reduces total departure delay by 49.4%, lowers average taxi time by up to 40.4%, and improves overall airport satisfaction by 5.2%, while reducing fairness deviation by 52.6%. These results demonstrate that the framework effectively enhances efficiency and equity in multi-airport departure operations.