Abstract—Over the last decade, air traffic flow at airports
experienced an increase never seen before. Whereas several
improvements have been achieved in enlarging the en-route
traffic capacity, little has been done in order to decrease
congestion on the airport surface. Aircraft taxiing is an
expensive process, responsible for causing delays for both
passengers and airlines and pollution problems. This paper
presents an optimization solution for aircraft taxi-scheduling
problem using Ant Colony Optimization, a method for search
and optimization inspired by the behavior of real ants in
nature. The simulations presented were based on real data
from Brasilia International Airport. However, the developed
model can be used in any airport for optimal taxiing routes
searching. The paper has shown the optimization of taxiing to
be efficient in achieving minimization of aircraft taxi time and
complies with security constraints at airports.
Index Terms—Ant algorithm, air traffic flow management,
optimization, simulation, taxiway sequencing.
The authors are with the TransLab, University of Brasilia, UnB, Brasilia,
DF, Brazil (e-mail: weigang@unb.br).
[PDF]
Cite:Using Ant Algorithm to Arrange Taxiway Sequencing in Airport, "Kamila B. Nogueira, Paulo H. C. Aguiar, and Li Weigang," International Journal of Computer Theory and Engineering vol. 6, no. 4, pp. 357-361, 2014.
