The takeoff process of a flight is affected by various uncertain factors,such as flight delay,scheduling delay and taxi time,etc. A reliable and robust departure sequence is essential to the safe and efficient operation of the airport. Firstly,the kernel probability density curve of flight delay is obtained by estimating the kernel density of flight de-lay historical data,and then the random number of flight delay is obtained by linear interpolation. Taking the ran-dom number of flight delay as input,a multi-runway departure flight scheduling model under the uncertain flight delay is established,and a genetic algorithm for encoding flight number is designed to solve this model. On this ba-sis,a multi-objective dynamic scheduling model under uncertain flight delay is further established,and a hybrid algorithm is designed to solve this model. Monte Carlo simulation is performed on the results of the two models to explore the impact of flight delay uncertainty on departure scheduling. Finally,taking the historical data of Guangzhou Baiyun International Airport as an example,the model validation is conducted.
flight delaykernel density estimationmulti-runway schedulinggenetic algorithm
维普
万方数据
