A bilevel flight collaborative scheduling model with traffic scenario adaptation: An arrival prior perspective

Abstract

Flight Optimization Scheduling (FOS) is a crucial component of decision-making support systems in air traffic management. This study addresses the hierarchical leader–follower relationship between arrival and departure flights and develops a bilevel flight collaborative scheduling model. The upper-level model focuses on scheduling arrival flights, while the lower-level model concentrates on scheduling departure flights. Given the varying demands across different traffic states, both the upper and lower-level models are driven by an efficiency objective during peak hours, namely, mitigating flight delays and improving runway throughput, correspondingly. Conversely, during non-peak hours, a trade-off between efficiency and fairness is sought. Furthermore, the lower-level model aims to maximize fairness among departure routes for all traffic states, leading to the formulation of a multi-objective programming model. To solve this proposed model, genetic algorithms are employed in conjunction with the elitism strategy and the forgetting mechanism. Experimental results demonstrate that the proposed model not only enhances the efficiency of flight and runway operations but also promotes fairness among flights and departure routes.