工业工程 ›› 2020, Vol. 23 ›› Issue (6): 117-123.doi: 10.3969/j.issn.1007-7375.2020.06.016

• 实践与应用 • 上一篇    下一篇

中小城市直达公交网络优化

曹振宇1,2, 蒋阳升1,2, 罗孝羚1,2, 杨洁1,2, 张姚1,2   

  1. 西南交通大学 1.交通运输与物流学院;
    2. 综合交通大数据应用技术国家工程实验室,四川 成都 610031
  • 收稿日期:2019-08-29 发布日期:2020-12-18
  • 作者简介:曹振宇(1995-),男,湖北省人,硕士研究生,主要研究方向为综合交通规划、智能交通
  • 基金资助:
    国家自然科学基金资助项目(51578465);重庆市交通运输工程重点实验室开放基金资助项目(2018TE04)

A Direct Optimization in Urban Transit Network for Small and Medium-sized Cities

CAO Zhenyu1,2, JIANG Yangsheng1,2, LUO Xiaoling1,2, YANG Jie1,2, ZHANG Yao1,2   

  1. 1. School of Transportation and Logistics;
    2. National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2019-08-29 Published:2020-12-18

摘要: 为了在非直达需求均能满足最少换乘的基础上进一步提高公交网络的直达率,建立了以直达率最大化和直达总时间最小化为目标的直达公交网络优化模型。与现有的研究相比,增加了换乘次数最小化约束,并采用具有遗传迭代机制的元启发式算法求解模型。利用Floyd算法求解初始网络最短路径,经线路删减、合并等操作后作为初始公交网络,使得模型具有高质量的初始解;通过space P法建模计算网络总换乘次数,在原有发车频率、最大车辆配备数、线路长度等约束下增加换乘次数最小化约束,采用频率共享规则进行客流分配,并与现有研究结果进行对比。结果表明,对于4条线路的Mandl's Swiss网络,在不考虑发车频率优化时,直达率较现有研究的试验1、2、3分别提高9.7%、8.41%和0.39%。

关键词: 公交网络优化, 直达公交网络, 元启发式算法, 最少换乘约束, 初始公交网络

Abstract: To improve the direct rate of transit network on the basis of transfer demand satisfied with the least transfer, a direct transit network optimization model with the goal of maximizing the direct rate and minimizing the total direct time was designed. Minimizing transfer times was discussed as constraint in the model compared with the existing research, and meta-heuristics algorithm that utilizes main operators similar to GA was applied for solutions. Floyd algorithm was used to find the shortest path of the initial transit network as initial transit network by decreasing routes or combining routes, so that the model obtained initial solution of high quality. Total transfer times of transit network was calculated by space P method, and minimizing transfer times was taken into account under the existing constraint conditions that contains frequencies, fleet size available, length of transit routes, and so forth, and then the demand was distributed to routes using frequency share rule. Comparing with the existing research results, the results show that the direct rate increases by 9.7%, 8.41% and 0.39% in the Mandall's Swiss network of four routes, compared with the experiment 1, 2 and 3 of the existing research without considering the optimization of frequencies.

Key words: transit network optimization, direct transit network, meta-heuristics algorithm, minimizing transfer times constraint, initial transit network

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