Abstract
Departure Management is responsible for creating a departure sequence of flights and for deciding which aircraft will takeoff firstly in scenarios of cancellation or delay. In many cases, this activity depends only on the experience of air traffic controllers who will empirically decide the departure sequence. This work presents two computational models to address the departure sequencing problem in airports according to Collaborative Decision Making. The first model is GeDMAN, a departure management system that uses Genetic Algorithm. The second one named as CoDMAN is based on the negotiation among the agents (aircraft) in a dynamic scenario using Game Theory. Both approaches are tested with real flight data from Brasilia International Airport. The simulation results show that the developed systems have the capability to manage the departure sequence automatically and reduce the total flight delay efficiently.
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Ferreira, D.M., Rosa, L.P., Ribeiro, V.F., de Barros Vidal, F., Weigang, L. (2014). Genetic Algorithms and Game Theory for Airport Departure Decision Making: GeDMAN and CoDMAN. In: Uden, L., Fuenzaliza Oshee, D., Ting, IH., Liberona, D. (eds) Knowledge Management in Organizations. KMO 2014. Lecture Notes in Business Information Processing, vol 185. Springer, Cham. https://doi.org/10.1007/978-3-319-08618-7_1
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DOI: https://doi.org/10.1007/978-3-319-08618-7_1
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