Research on the Application of PSO Algorithm in Aviation Control Flight Plan Path Search

In the field of aviation, the search for air traffic control flight paths is a key issue for flight operators. The principal objective is to search for the optimal path in order to minimize the flight time and fuel consumption, and to enhance flight efficiency in terms of environmental and economical aspects. In this paper, the performance of PSO Algorithm and Genetic Algorithm in the search for air traffic control flight paths is presented and discussed, respectively. The differences in the advantages and discoveries between the two algorithms in seeking optimal route are well displayed. In this section of the paper, global search capability, efficiency of optimization, and convergence are analyzed and compared between PSO Algorithm and GA. According to the test results, the PSO Algorithm has better fuel saving effect for the flights on the same route than GA. That is to say, the PSO Algorithm has advantages on global search, convergence, and performance on normal trip. Meanwhile, parameter adjustments to the PSO Algorithm had certain impacts on the performance of the PSO Algorithm.

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Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/icsece61636.2024.10729465
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50
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article

Research on the Application of PSO Algorithm in Aviation Control Flight Plan Path Search

Bing Xu
2 citations
Robotic Path Planning Algorithms
0.50
article

Research on the Application of PSO Algorithm in Aviation Control Flight Plan Path Search

Bing Xu
article en
2 citations

Abstract

In the field of aviation, the search for air traffic control flight paths is a key issue for flight operators. The principal objective is to search for the optimal path in order to minimize the flight time and fuel consumption, and to enhance flight efficiency in terms of environmental and economical aspects. In this paper, the performance of PSO Algorithm and Genetic Algorithm in the search for air traffic control flight paths is presented and discussed, respectively. The differences in the advantages and discoveries between the two algorithms in seeking optimal route are well displayed. In this section of the paper, global search capability, efficiency of optimization, and convergence are analyzed and compared between PSO Algorithm and GA. According to the test results, the PSO Algorithm has better fuel saving effect for the flights on the same route than GA. That is to say, the PSO Algorithm has advantages on global search, convergence, and performance on normal trip. Meanwhile, parameter adjustments to the PSO Algorithm had certain impacts on the performance of the PSO Algorithm.

Air Force Engineering University (CN)
Openalex Percentile: Top 34%
Robotic Path Planning Algorithms
0.50
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