Research On Dynamic Stochastic Distribution Strategy Of Multi-airport Arrival And Departure Flow

When air traffic congestion occurs, to ensure flight safety, to reduce flight delay costs and toraise the utilization ratio of airspace resources are an issue of great concern in the process of civilaviation research. The implementation of the ground holding strategy can effectively reduce flightdelays and airlines’ economic losses. However, the present research on Ground Holding Program hasnot been able to involve the three important issues of the uncertainty of airport capacity, the balancebetween arrival traffic flow and departure traffic flow and the correlation between the multi-airport atthe same time, and the execution efficiency of Ground Holding Program is low. Therefore, we need tostart a research on the dynamic and stochastic distribution strategy of multi-airport arrival anddeparture traffic flow.On the basis of previous study, this paper made a deep research on the dynamic and stochasticdistribution strategy of multi-airport arrival and departure traffic flow. First, based on the conversioncurve of arrival-departure capacity and collaborative decision-making theory, we studied thecollaborative allocation strategy of single-airport arrival and departure traffic flow, optimized arrivaland departure traffic flow, and co-allocated flight arrival and departure time, in order to avoid flightdelays and decrease the air traffic congestion in strategic level. Then, we introduced the concept of thecapacity scenario tree to describe the uncertainty of airport capacity, and studied the dynamic andstochastic distribution strategy of multi-airport arrival and departure traffic flow, to provide real-timeand dynamic airport arrival and departure traffic flow optimization schedule to ATC department andreduce the total expected flight delay cost. On the basis of the above study, we extended the number ofthe airport with limited capacity, and discussed the dynamic and stochastic distribution strategy ofmulti-airport arrival and departure traffic flow, and integrated weather forecast information into themodel to construct airport capacity scenario tree network, then designed the genetic algorithm tocompute the arrival and departure traffic flow optimization schedule of a given airport network.Finally, the system of the dynamic and stochastic distribution strategy of multi-airport arrival anddeparture traffic flow was designed and realized, and the simulation examples verified the validity andpracticability of the proposed strategy.