Optimization algorithm of urban rail transit operation scheduling based on linear programming

被引：0
|
作者：
Wang Q.-Y. [1 ]
Qu W.-Q. [2 ]
机构：
[1] School of Mechanical and Electronic Control Engineering, Beijing Jiaotong University, Beijing
[2] School of Information Science and Technology, Fudan University, Shanghai
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2023年 / 53卷 / 12期
关键词：
computer technology; dispatch optimization model; linear planning; passenger flow features; track traffic characteristics; urban rail transit;
D O I：
10.13229/j.cnki.jdxbgxb.20221275
中图分类号：
学科分类号：
摘要：
In order to improve the overall travel efficiency of urban rail transit，an optimization algorithm for urban rail transit operation scheduling based on linear programming was proposed. By extracting the characteristics of rail transit road conditions and passenger flow，a scheduling optimization model that fits the actual situation was established. Linear programming was used to transform the scheduling optimization model into an integrated scheduling optimization model for urban rail transit with significantly reduced infinite discretization probability. The experimental results show that the average delay time after optimization of the proposed method is reduced by 17 min，the travel time of passengers is reduced by 25 min，and the coincidence rate between rail stations and passenger flow demand points is high，indicating that the scheduling effect of the method is good. © 2023 Editorial Board of Jilin University. All rights reserved.
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页码：3446 / 3451
页数：5
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  • [1] Zhou Kang, Song Rui, Peng Yan, Current situation and countermeasures of comprehensive land develop⁃ ment for urban rail transit, Urban Rapid Rail Tran⁃ sit, 33, 2, pp. 20-24, (2020)
  • [2] He Sheng-xue, Bi-level programming model and algorithm for traffic flow assignment considering desti⁃ nation selection, Journal of Wuhan University of Technology (Transportation Science & Engineering), 43, 4, pp. 596-600, (2019)
  • [3] Lai Yuan-wen, Zhang Jie, Urban bus scheduling opti⁃ mization based on simulated anneal-adaptive cuckoo search algorithm, Journal of Transportation Systems Engineering and Information Technology, 21, 1, pp. 183-189, (2021)
  • [4] Liu Hui, Dai Xue-wu, Cui Dong-liang, Et al., Opti⁃ mization of high-speed train operation scheduling based on parameter adaptive improved ant colony algorithm, Control and Decision, 36, 7, pp. 1581-1591, (2021)
  • [5] Ma Chao-qun, Zhang Shuang, Chen Quan, Et al., Characteristics and vulnerability of rail transit network besed on perspective of passenger flow characteristics, Journal of Traffic and Transportation Engineer⁃ ing, 20, 5, pp. 208-216, (2020)
  • [6] Da Cheng, Qian Yong-sheng, Zeng Jun-wei, Et al., A study on the evaluation of urban rail transit network structure, Railway Transport and Economy, 42, 2, pp. 122-127, (2020)
  • [7] Song Li-jing, Bai Tong-zhou, He Yu-long, Et al., Feeder bus routes and frequency optimization based on mixed integer nonlinear programming, Journal of Transportation Systems Engineering and Informa⁃ tion Technology, 22, 3, pp. 104-111, (2022)
  • [8] Zhou Xi-hua, Jia Hong-xin, Huang Xiao-hong, Et al., Model and algorithm of the bi-level multiple fol⁃ lowers linear programming with trapezoidal fuzzy deci⁃ sion variables, Chinese Journal of Engineering Mathematics, 38, 1, pp. 49-62, (2021)
  • [9] Xu Wei-hua, Guo Hai-feng, Distributed cooperative vehicle scheduling simulation under different traffic flow conditions, Computer Simulation, 37, 7, pp. 178-182, (2020)
  • [10] Jia Hong-fei, Ding Xin-ru, Yang Li-li, Bi-level pro⁃ gramming model for optimization design of tidal lane, Journal of Jilin University(Engineering and Tech⁃ nology Edition), 50, 2, pp. 535-542, (2020)
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