Paper
14 February 2024 Research on optimization of green route network
Kexin Niu, Guifang Li, Xiao Huang, Yong Tian
Author Affiliations +
Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 1301857 (2024) https://doi.org/10.1117/12.3024755
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
The optimization research on air route networks is significant in achieving low-carbon and environmentally friendly operations. However, existing studies on air route networks often lack consideration for this objective. To address this gap, this study conducts an in-depth analysis of the existing problems in the air route networks in the central and southern regions. Based on this analysis, a green air route network optimization model is constructed, comprehensively considering the operational costs, flight conflicts, and emissions of greenhouse gases and pollutants in the aviation sector. Genetic algorithms are employed to solve the optimization model. The empirical analysis is then conducted using a selected portion of the air route networks in the central and southern regions. The experimental results demonstrate that the optimized air route network can significantly reduce operational costs and environmental impacts. Specifically, the optimized air route network achieves a 6.18% reduction in operational costs and a 6.20% decrease in greenhouse gas and pollutant emissions. Although the change in the flight conflict coefficient is minimal, there is overall improvement, thus validating the effectiveness of the proposed model.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Kexin Niu, Guifang Li, Xiao Huang, and Yong Tian "Research on optimization of green route network", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 1301857 (14 February 2024); https://doi.org/10.1117/12.3024755
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KEYWORDS
Atmospheric modeling

Mathematical optimization

Particle swarm optimization

Genetic algorithms

Safety

Carbon dioxide

Image segmentation

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