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Publishing Language: Chinese

Optimization of Train Planning for General Tree-Type Line

Runbin WEI1Shunping JIA1,2( )Ruiyong TONG1Shujing ZHANG1
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
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Abstract

In the background of rail transit network operation, the simple line and routing forms can no longer meet the diverse passenger travel demand. Therefore, in order to cope with the mismatch between traffic supply and demand brought about by passenger trips in complex directions, the paper proposed a rail transit line form of general Tree-type line based on the existing research on Y-type lines, and it was divided into diameter type and radius type with reference to the actual operating line cases. Firstly, the paper designed a line topology form of Tree-type line and established a multi-routing planning optimization model for Tree-type line by considering the distribution of passengers among different trains and taking the departure frequency as the decision variable and the passenger travel time and minimum operating cost as the target function. Then it designed and solved the non-dominant ranking genetic algorithm (NSGA-Ⅱ) with the elite strategy. The model and algorithm were validated using the RER A line in Paris as an example. Finally, the optimization scheme was compared with the split-line scheme. The results show that: the algorithm can find the Pareto frontier solutions of the train planning, and the travel time of passengers and the operation cost of enterprises show a significant negative correlation; the obtained optimization scheme has a significant reduction in the travel time of passengers and the operation cost of enterprises compared with the split-line scheme. It reduces the waiting time of passengers by 1.76% to 12.90%, the transfer time of passengers by 33.63% to 34.98%, the total running kilometres of trains by 7.69% to 21.67%, and the the number of trains on the line by 9 to 19.

CLC number: U292.42 Article ID: 1000-565X(2022)11-0044-08

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Journal of South China University of Technology (Natural Science Edition)
Pages 44-51

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Cite this article:
WEI R, JIA S, TONG R, et al. Optimization of Train Planning for General Tree-Type Line. Journal of South China University of Technology (Natural Science Edition), 2022, 50(11): 44-51. https://doi.org/10.12141/j.issn.1000-565X.220140

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Received: 17 March 2022
Published: 25 November 2022
© Journal of South China University of Technology(Natural Science Edition)