Network Flow Optimization Under Uncertain Capacity

In order to ensure the aircraft flying safely and reduce flight delays,it is necessary to make reasonable flight plans.However,due to uncertain factors such as weather,military activities and equipment failure,the airport/sector capacity is dynamic.The deterministic network flow optimization model regards the stochastic airspace capacities as deterministic values,airport/sector capacity may be larger or smaller than predicted value,leading to flight slot change.In order to mitigate the impact of capacity uncertainty on flight operation,this paper proposes a flow optimization model under uncertain capacity,and uses chance constraints to deal with capacity uncertainty.This paper mainly includes four parts:(1)Establish the deterministic and probabilistic network flow optimization models;(2)Improve the chance-constrained method.Traditional chance-constrained method aims at the whole network,which makes it difficult to solve the model.This paper sets the chance-constrained value for each node,which significantly improves the calculation speed of the model;(3)Combining node importance with uncertainty model,for the first time,the opportunity constraints are set according to the importance of nodes;(4)Finally,a variety of capacity scenarios are set up to calculate the difference between the departure/ arrival time and the allocated slot under each scenario,the allocation schemes in each scenario are compared with each other,the results show that considering the uncertainty of capacity makes the allocation scheme more anti-jamming,and considering the importance of nodes can further improve the anti-jamming performance of the scheme.The results of this paper are of great significance to the optimization of network flow with uncertain capacity and the development of air traffic flow management system.