1 research outputs found
Multiairport capacity management: genetic algorithm with receding horizon
The inability of airport capacity to meet the growing
air traffic demand is a major cause of congestion and costly delays.
Airport capacity management (ACM) in a dynamic environment
is crucial for the optimal operation of an airport. This paper
reports on a novel method to attack this dynamic problem by
integrating the concept of receding horizon control (RHC) into a
genetic algorithm (GA). A mathematical model is set up for the
dynamic ACM problem in a multiairport system where flights can
be redirected between airports. A GA is then designed from an
RHC point of view. Special attention is paid on how to choose those
parameters related to the receding horizon and terminal penalty.
A simulation study shows that the new RHC-based GA proposed
in this paper is effective and efficient to solve the ACM problem in
a dynamic multiairport environment