Minimizing airline and passenger delay cost in airport surface and terminal airspace operations

This research studies the effectiveness of incorporating airline and passenger delay cost (APDC) into an integrated airport surface and terminal airspace (ASTA) traffic management system. Most air traffic management systems typically schedule aircraft with an assumption that all flights want to be operated along the minimum fuel trajectory. However, airlines and passengers may have other preferences that can significantly influence flight schedules. Therefore, the objective of this research is to investigate the effect of incorporating APDC to ASTA scheduling, while ensuring safety. A mixed integer nonlinear programming model (MINLP-APDC) and a swap separation violating aircraft heuristic model (SSVA-APDC) are developed to minimize the cost of delays for airlines and passengers. The proposed approaches are compared to the first-come, first-serve heuristic and two integrated scheduling algorithms for ASTA operations: 1) minimizing runway makespan (MINLP-RM); and 2) minimizing flight delays (MINLP-FD). The experimental results show that the proposed approaches save at least 1.2% APDC compared to other approaches. The proposed approaches can also achieve at least 3.0% fewer flight delays than the MINLP-RM model without increasing either runway or schedule makespan. Compared to MINLP-FD, the MINLP-APDC model increases flight delays by on average 3.7% while the SSVA-APDC model achieves on average 15.1% more flight delays. Although the MINLP-APDC model outperforms the SSVA-APDC heuristic in terms of APDC and flight delays, it requires more than 30 min of computational time. Meanwhile, the SSVA-APDC heuristics requires only a few seconds to provide a feasible flight schedule, which makes it more practical.