Arriving Flow Management Using Evolutionary Algorithm in a 4D Environment
- Daniel Alberto Pamplona
- João Luiz de Castro Fortes
- Vitor Filincowsky
- Debora Mendes
- Li Weigang
- Claudio Jorge Pinto Alves
Aeronautics Institute of Technology – Department of Air Transportation / University of · Aeronautics Institute of Technology – Department of Air Transportation · University of Brasilia – Translab, Department of Computer Science
- Evento
- XVI SITRAER – Rio de Janeiro, RJ, Brasil, 25 a 27 de outubro de 2017
- Volume
- Proceedings of XVI Air Transportation Symposium (SITRAER) · ISSN 2448-1912
- Páginas
- 752–762
- Editora
- Universidade Federal do Rio de Janeiro (UFRJ/COPPE)
- Editores
- Fabio Krykhtine
Abstract
The aim of this article is to use an Evolutionary Algorithm (EA) for arriving flow management in order to solve the problem of arrival scheduling and sequencing (ASS). To evaluate the effectiveness of the proposed model, it was used actual data from Guarulhos International Airport (SBGR). Simulation results show that the method proposed decreased delay when compared to the current sequencing operations. The introduction of this technique represents a shift from the current arrival sequence model to a Trajectory-Based Operations based model in the Air Traffic Flow Management (ATFM), balancing air traffic demand with airspace capacity to ensure the most efficient use of the airspace system.
Keywords: Air Traffic Flow Management; Evolutionary Algorithm; Arrival Management; Intelligent System