Meta-Heuristics Approach for Arrival Sequencing and Delay Absorption through Automated Vectoring
Résumé
The continuous increase in air traffic compels
major airports to optimize their resources and enhance their
Terminal Maneuvering Airspace (TMA) operations. The pri-
mary constraint to increasing airport capacity is the required
separation minima between pairs of aircraft arriving through
the same approach routes. RECAT-EU is a revised global wake
separation minima scheme released by EUROCONTROL in
2018. This suggested a reduction in separation minima between
certain aircraft pairs while maintaining safety levels. However, it
increases in separation minima scheme complexity by doubling
the number of non-minimum radar separation (MRS) values.
In this work, a Meta-Heuristic based optimization model is
proposed to sequence arrival flights based on the RECAT-EU
separation scheme, which can provide an optimized vectoring
to ensure flights absorb their assigned delays before reaching
the final approach fix. Findings show that the proposed model
is able to generate an optimized landing sequence for 50 arrival
flights in a computation time of 16 seconds. It also suggests that
the proposed algorithm’s computational time increases linearly
with increasing the number of flights. Furthermore, trajectory
vectoring results demonstrate that 85% of the assigned delays
could be absorbed by flying the proposed vectored trajectories.