Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network


Cong Qiao, Qifeng Gao, Huayan Xing, Journal of Information Processing Systems Vol. 19, No. 1, pp. 46-54, Feb. 2023  

https://doi.org/10.3745/JIPS.04.0263
Keywords: Ant Colony, Convolutional Neural Network, Layout Optimization, Railway, Transportation, Transportation Route
Fulltext:

Abstract

To improve the railway transportation capacity and maximize the benefits of railway transportation, a method for layout optimization of railway transportation route based on deep convolution neural network is proposed in this study. Considering the transportation cost of railway transportation and other factors, the layout model of railway transportation route is constructed. Based on improved ant colony algorithm, the layout model of railway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual information of railway transportation routes, optimization of the candidate railway transportation routes obtained by the improved ant colony algorithm was performed based on deep convolution neural network, and the optimal railway transportation routes were output, and finally layout optimization of railway transportation routes was realized. The experimental results show that the proposed method can obtain the optimal railway transportation route, the shortest transportation length, and the least transportation time, maximizing the interests of railway transportation enterprises.


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Cite this article
[APA Style]
Qiao, C., Gao, Q., & Xing, H. (2023). Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network. Journal of Information Processing Systems, 19(1), 46-54. DOI: 10.3745/JIPS.04.0263.

[IEEE Style]
C. Qiao, Q. Gao, H. Xing, "Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network," Journal of Information Processing Systems, vol. 19, no. 1, pp. 46-54, 2023. DOI: 10.3745/JIPS.04.0263.

[ACM Style]
Cong Qiao, Qifeng Gao, and Huayan Xing. 2023. Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network. Journal of Information Processing Systems, 19, 1, (2023), 46-54. DOI: 10.3745/JIPS.04.0263.