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Genetic Algorithms and Game Theory for Airport Departure Decision Making: GeDMAN and CoDMAN

  • Deborah Mendes Ferreira
  • Lucas Pessoa Rosa
  • Vitor Filincowsky Ribeiro
  • Flávio de Barros Vidal
  • Li Weigang
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 185)

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.

Keywords

Airport Collaborative decision making Departure management Game theory Genetic algorithm 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Deborah Mendes Ferreira
    • 1
  • Lucas Pessoa Rosa
    • 1
  • Vitor Filincowsky Ribeiro
    • 1
  • Flávio de Barros Vidal
    • 1
  • Li Weigang
    • 1
  1. 1.TransLab, Department of Computer ScienceUniversity of BrasiliaBrasilia – DFBrazil

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