Modeling the swarm optimization to build effective Continuous Descent Arrival sequences

The main goal in Continuous Descent Arrival (CDA) operations is the management of flight trajectories in order to optimize the operating capability of the aircraft in Terminal Manoeuvring Area (TMA), reducing fuel burn and emissions during the descent/approach phase. At the same time the maximization of airspace efficiency/capacity needs to be addressed considering local airspace requirements and constraints. The arrival coordination task can be viewed as a scenario in which several aircraft approach at a common merging point within optimum time windows, ensured by ATC in order to eliminate en-route conflicts with an adequate sequencing of the arrivals. It is proposed a 4D-compliant framework that integrates the individual performance preferences of the landing aircraft and the ATC arrival management procedures. The ATC agent should use a particle swarm optimization algorithm in order to build valid, safe arrival sequencing that decreases and distributes the overall operational costs among the aircraft in a fair and efficient manner. Using actual data from Brasilia International Airport (SBBR) to evaluate the effectiveness of the proposed modeling, a case study shows that 77% of the flights are able to accomplish their desired time window flying a CDA procedure.