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
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