Aircraft rerouting and rescheduling in multi-airport terminal area under disturbed conditions

The disturbances, caused by resource competition, weather changes, and demand uncertainties, frequently occur and result in obvious fluctuations (e.g., the increase or decrease of demand and capacity) in demand and capacity. This work addresses the problem of aircraft rerouting and rescheduling in presence of disturbances, characterized by the increase or decrease of demand and capacity, at a multi-airport terminal maneuvering area (TMA). A multi-objective optimization model is proposed to minimize the total flight delays and total extra flying time, considering the aircraft wake turbulence separation, runway operation rules, air traffic control regulations, scheduling time windows, and airport/airspace capacity, etc. Based on the non-dominated sorting genetic algorithm (NSGA-II), we designed an efficient evolutionary algorithm to solve the proposed model and search the Pareto solutions. Five scenarios are designed to analyze and compare the operation performance under normal and disturbed conditions, using the classic First-Come-First-Served (FCFS) and optimized scheduling (OPTS) methods. A case study is conducted for Shanghai Pudong and Hongqiao Airports, and the computational results show that, compared with the FCFS method, the proposed OPTS method significantly performs a overall better performance in minimizing total flight delay and total extra flying time, while slightly inferior in optimizing the delay and extra flying time of one single flight