An evaluation method of departure flight normal rate

Flight delays have become the main research objective for airports to improve efficiency and control costs, as an important indicator to measure flight delays, departure flight normal rate (DFNR) plays a more crucial role in influencing airport planning decisions. Theoretical research mainly focuses on reducing total delays, simulation methods can not consider delays caused by non-ground operation limitations, resulting in too ideal DFNR. In order to evaluate DFNR better in the airport's planning and operational schemes, this paper proposes an evaluation method for DFNR, which models the probability distribution of flight delay caused by various uncertain factors, and combines the departure delay from AIRTOP simulation caused by the ground operational restrictions of airport. The genetic algorithm is used to solve the various parameters in the model. Taking an airport for example, the DFNRs of 10 situations is calculated. The results show that the number of delay factors has a relatively small impact on the results, the calculation results of proposed model are consistent with the expected results and can better reflect the differences of situations compared to simulation, so the calculation results of proposed model are more reasonable and can be used as a decision-making reference. Besides, the value of delay threshold has a significant impact on the calculation results of DFNR.