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1122. Civil aviation route-planning method based on improved restricted searching area algorithm
Invited abstract in session TC-28: Advancements of OR-analytics in statistics, machine learning and data science 6, stream Advancements of OR-analytics in statistics, machine learning and data science.
Tuesday, 12:30-14:00Room: 065 (building: 208)
Authors (first author is the speaker)
| 1. | Zhang Miaomiao
|
| Information Center, China Southern Airlines Company Limited | |
| 2. | Nan Xu
|
| China Southern Airlines Company Limited |
Abstract
In order to address the large calculation scale and slow route-planning speed problems caused by the large global aviation network and complicated restrictions, this paper proposed an improved algorithm for route-planning within hybrid restricted searching area. Firstly, a machine learning algorithm was used to optimize the major axis parameter of the ellipse in the ellipse restricted searching area algorithm by analyzing the historical flight plan data. Then, based on the rectangle restricted searching area algorithm and the ellipse restricted searching area algorithm, the proposed algorithm considered restrictions on the search direction to further reduce the search scale and improve the search efficiency. Experiments show that compared with ellipse restricted searching area algorithm, the hybrid restricted searching area algorithm reduces the search size by about 50% and the total execution time by 34% on average, which verifies the effectiveness of the method.
Keywords
- Airline Applications
- Machine Learning
- Algorithms
Status: accepted
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