Resilience assessment and recovery of airport departure flights under severe weather

In order to ensure the overall performance of the airport under severe weather, scientifically evaluate the resilience of the airport's flight operations, improve flight recovery capabilities, and alleviate the impact of severe weather effectively. This article first gives the definition of airport departure flight operation. Starting from the performance of the airport departure flight operation system, it analyzes flight departure delay time, total departure delay time, departure flight normality rate and departure airport flight operation system comprehensive resilience index four indicators to evaluate the resilience changes of the system under severe weather conditions; put forward the concept of the performance recovery strategy of the airport departure flight operation system, and established the corresponding resilience model, and used the genetic algorithm to optimize the sequence of the delayed departure flights; finally, take the "721" heavy rain event in Beijing Capital International Airport in 2012 as an example to analyze the data, obtain the performance index and resilience index of the Capital Airport under the influence of heavy rain, and use the optimized departure flight schedule to compare and analyze the changes in airport departure flight operating system performance and resilience level. The results indicate that: under the influence of heavy rain, the comprehensive resilience index of the airport departure flight operation system decreased from 0.4573 to 0.0628 , and increased to 0.2223 after the rainstorm decreased; after the flight optimization and sequencing was carried out in the recovery stage of the airport departure flight operation performance, the total number of departure flights decreased. The delay time is reduced by 24.85%, the airport performance recovery speed is increased by 13.89%after optimization, and the minimum resilience index of the optimized airport departure flight operation system is increased by 13.38%, and under the same heavy rain, the system performance is given priority to restore to the initial state, indicating that the evaluation Indicators are valid.