International Journal of Computational Intelligence Systems

Volume 9, Issue 3, June 2016, Pages 559 - 571

Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm

Authors
Adel Soheili1, soheiliadel@stu.um.ac.ir, Habib Rajabi Mashhadi1, 2, *, h_mashhadi@um.ac.ir
*Corresponding author
Corresponding Author
Habib Rajabi Mashhadih_mashhadi@um.ac.ir
Received 14 November 2015, Accepted 24 January 2016, Available Online 1 June 2016.
DOI
10.1080/18756891.2016.1175818How to use a DOI?
Keywords
Air traffic control; arriving sequences delays; traffic management advisor; genetic algorithm
Abstract

During the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational burden, higher convergence rate and lower overall delays. Comprehensive simulations and implementation of the imbedded specially designed rearrangement operator, have shown the effectiveness of the proposed method in comparison with previous literatures and classic GA.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 3
Pages
559 - 571
Publication Date
2016/06/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1175818How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Adel Soheili
AU  - Habib Rajabi Mashhadi
PY  - 2016
DA  - 2016/06/01
TI  - Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm
JO  - International Journal of Computational Intelligence Systems
SP  - 559
EP  - 571
VL  - 9
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1175818
DO  - 10.1080/18756891.2016.1175818
ID  - Soheili2016
ER  -