工业工程

工业工程 ›› 2017, Vol. 20 ›› Issue (5): 51-57.doi: 10.3969/j.issn.1007-7375.e17-2065

• 专题论述 • 上一篇    下一篇

全局视角下的南京地铁网络拓扑结构比较

蔡虹1,2, 徐腾飞3, 朱金福1   

  1. 1. 南京航空航天大学 民航学院, 江苏 南京 211106;
    2. 南京工业大学 经济与管理学院, 江苏 南京 210094;
    3. 西南交通大学 土木工程学院, 四川 成都 610031
  • 收稿日期:2017-03-22 出版日期:2017-10-30 发布日期:2017-11-17
  • 作者简介:蔡虹(1978-),女,浙江省人,讲师,博士研究生,主要研究方向为交通运输与物流及供应链管理.
  • 基金资助:
    江苏省2016年度高校哲学社会科学研究一般项目资助（2016JB630029）；南京工业大学2016青年社科基金资助项目（qnsk2016014）；南京工业大学教育部社科基金未立项扶持项目（ZX17442520001）

A Comparative Study of the Topological Structure of Nanjing Metro Network Based on the Whole Perspective

CAI Hong1,2, XU Tengfei3, ZHU Jinfu1   

  1. 1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
    2. Economy and Management School, Nanjing Tech University, Nanjing 210094, China;
    3. College of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2017-03-22 Online:2017-10-30 Published:2017-11-17

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摘要： 基于复杂网络理论，从全局视角出发，针对南京地铁2016年实际运营网络及2021年规划运营网络分别构建SpaceL拓扑结构模型，并针对地铁网络的平面特征，应用节点度及其分布、平均最短距离及其分布、网络直径、介数及联通度指标对其结构特性进行分析比较。研究结果表明，2016与2021年地铁运营网络均具有无标度特性，节点度指数分别为4.2与3.7，2021年地铁网络肥尾特征更明显，且hub点发生较大变化；2021较2016年地铁网络联通度有所提高，但都不到0.4，且网络平均最短距离均大于其网络顶点数目的对数，因此不具备小世界网络的特征。根据结论提出正确识别一个网络的关键节点，有必要将网络本身的静态结构与代表动态结构的流量因素综合考虑；其次衡量地铁网络的发展程度时，需将覆盖区域面积加以考虑，单纯考虑联通度值不够准确。此研究对进一步研究南京地铁网络鲁棒性、易损性、可恢复性进而优化其资源配置、加强风险管理具有重要意义。

关键词: 南京地铁网络, SpaceL拓扑模型, 节点度分布, 平均最短距离, 网络联通度

Abstract: Based on the complex network theory, SpaceL topology models of 2016 and 2021 Nanjing Metro network were set up, and the indexes as node degree distribution, average shortest-path length, network diameter and degree of connectivity were adopted to make a comparative study of their structural property, according to planar characteristic of the metro network. The results showed that Nanjing Metro Network of 2016 and 2021 had scale-free property, and the scale-free factor were 4.2 and 3.7 respectively, and the “fat tail” was more obvious in that of 2021; both the degree of connectivity of 2016 and 2021 were below 0.4, plus the network average shortest-path length were not below the log of the number of vertex, so the network had no small-world property; according to betweenness, the key stations change a lot in 2016 and 2021. According to the results, it is proposed that it be necessary to combine the flow pattern with the network static structure to identify the key nodes, the line-covering area should also be considered when measuring the developing stage of the metro network. The research was fundamental endeavor to reveal the robustness, vulnerability, resilience of Nanjing Metro Network, and to optimize allocation of resources，and to strengthen risk management.

Key words: Nanjing metro network, SpaceL topology model, node degree distribution, average shortest-path length, degree of connectivity

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