Dynamic airspace sectorization via improved genetic algorithm
This paper deals with dynamic airspace sectorization (DAS) problem by an improved genetic algorithm (iGA). A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5%, the coordination workload index is reduced by 11.2%, and the sector average flight time index is increased by 11.4% during the peak-hour traffic.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/2095087X
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Supplemental Notes:
- © 2013 Yangzhou Chen et al.
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Authors:
- Chen, Yangzhou
- Bi, Hong
- Zhang, Defu
- Song, Zhuoxi
- Publication Date: 2013
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 117-124
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Serial:
- Journal of Modern Transportation
- Volume: 21
- Issue Number: 2
- Publisher: Springer Verlag
- ISSN: 2095-087X
- Serial URL: http://jmt.swjtu.edu.cn/EN/volumn/home.shtml
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Air traffic control; Airspace (Aeronautics); Flight time; Genetic algorithms; Peak periods; Workload
- Geographic Terms: China
- Subject Areas: Aviation; Planning and Forecasting; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01492838
- Record Type: Publication
- Files: TRIS
- Created Date: Sep 13 2013 7:42AM