The flight departure process is affected by various uncertain factors,such as flight delays,scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient ope...The flight departure process is affected by various uncertain factors,such as flight delays,scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient operation for airports. An optimal scheduling model for multi-runway departure considering the arrival aircraft crossing departure runway is developed. A genetic algorithm encoding flight numbers is designed to find a near-optimal solution. After that,further establish a multi-objective dynamic scheduling model and design a hybrid algorithm to solve it,and compare and analyze the results of the two models. A quantitative analysis of departure time based on the kernel density estimation is performed,and Monte Carlo simulations are carried out to explore the impact of flight departure time’s uncertainty on departure scheduling. The results based on historical data from Guangzhou Baiyun Airport are presented,showing the advantage of the proposed model and algorithm.展开更多
基金supported by the Open Fund for Graduate Innovation Base of Nanjing University of Aeronautics and Astronautics(No. kfjj20190726)。
文摘The flight departure process is affected by various uncertain factors,such as flight delays,scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient operation for airports. An optimal scheduling model for multi-runway departure considering the arrival aircraft crossing departure runway is developed. A genetic algorithm encoding flight numbers is designed to find a near-optimal solution. After that,further establish a multi-objective dynamic scheduling model and design a hybrid algorithm to solve it,and compare and analyze the results of the two models. A quantitative analysis of departure time based on the kernel density estimation is performed,and Monte Carlo simulations are carried out to explore the impact of flight departure time’s uncertainty on departure scheduling. The results based on historical data from Guangzhou Baiyun Airport are presented,showing the advantage of the proposed model and algorithm.
