Short-term En route Air Traffic Flow Management Under Departure and Wind Uncertainties with a Heuristic and Greedy Solution Approach

The importance of short-term air traffic flow management can never be depreciated due to the associated demand uncertainty which is caused by the dynamicity in the air transportation systems. Ideally, the flight plans require frequent fine-tuning depending on the dynamic network changes such as flight time deviations, weather conditions, etc.. Motivated by this, the paper incorporates the effect of departure time uncertainty and wind uncertainty in short-term flight routing and scheduling. The en route capacities are utilized while ensuring safety in terms of maintaining required in-trail-separation between aircraft, avoiding capacity violations as well as merging conflicts due to uncertainty of demand. The proposed model effectively manages the uncertainty in the network by utilizing short-term planning horizons and further, more accurate real-time wind forecast data are incorporated in optimizing the flight schedules. To generate flight schedules with a less time-complexity, we use a heuristic approach with parallel computation while decomposing the problem into maximum independent sets. The proposed model is experimentally validated for the applicability via realistic air traffic data.