测绘学报 ›› 2019, Vol. 48 ›› Issue (1): 86-94.doi: 10.11947/j.AGCS.2019.20180007

• 地图学与地理信息 • 上一篇    下一篇

面向大规模道路网的最短路径近似算法

张志然1,2, 刘纪平2,3, 仇阿根2, 钱新林2, 张福浩2   

  1. 1. 武汉大学资源与环境科学学院, 湖北 武汉 430079;
    2. 中国测绘科学研究院, 北京 100830;
    3. 河南省科学院地理研究所, 河南 郑州 450052
  • 收稿日期:2018-01-03 修回日期:2018-09-20 出版日期:2019-01-20 发布日期:2019-01-31
  • 通讯作者: 刘纪平 E-mail:liujp@casm.ac.cn
  • 作者简介:张志然(1991-),女,博士生,研究方向为空间数据分析与挖掘。E-mail:zzranature@163.com
  • 基金资助:

    国家重点研发计划(2016YFC0803108);国家基础测绘科技项目(2018KJ0104)

The shortest path approximation algorithm for large scale road network

ZHANG Zhiran1,2, LIU Jiping2,3, QIU Agen2, QIAN Xinlin2, ZHANG Fuhao2   

  1. 1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;
    2. Chinese Academy of Surveying and Mapping, Beijing 100830, China;
    3. Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China
  • Received:2018-01-03 Revised:2018-09-20 Online:2019-01-20 Published:2019-01-31
  • Supported by:

    The National Key Research and Development Program of China (No. 2016YFC0803108);The National Basic Surveying and Mapping Technological Project (No. 2018KJ0104)

摘要:

节点重要性对大规模道路网下最短路径的计算有着重要影响。本文提出了顾及节点重要性的最短路径估计方法,该方法基于Critic方法与复杂网络理论评价节点的重要性,结合限制策略实现网络划分,通过层次结构网络的构建,实现大规模道路网数据的有效化简和最短路径的快速有效计算。试验结果表明,该方法能够使中心节点均衡地分布于网络,更好地均衡划分后子网络的规模;随着限制参数的增大,网络规模逐渐降低,查询精度最高达到1.026,相比于单一指标和无限制参数的方法,本文方法显著降低了网络的规模,在最短路径的近似计算上保持了较高的准确性,为大规模复杂网络的近似分析提供分析思路。

关键词: 大规模道路网, 最短路径, 节点重要性, 网络划分

Abstract:

Node importance has significant influence on the calculation of shortest path of large-scale road network. A shortest path estimation method based on node importance is proposed in this paper that is suitable for large-scale network. This method integrates the criteria importance though intercrieria correlation (CRITIC) method with complex network theory, with a view to evaluate nodes importance. By combining the restriction strategy to realize network division, the effective simplification of large-scale road network and shortest path estimation are realized through the construction of hierarchical network. The results show that this method can be used to distribute the center nodes evenly, and make little difference in the size of the subnetwork. As the constraint parameter increases, the numbers of nodes and edges reduced gradually, and the query accuracy reached 1.026. Compared with single index and unlimited parameters methods, this paper significantly reduces the size of the network and obtains a high accuracy on the approximate calculation of the shortest path. These will provide a new way of thinking for approximate analysis of large-scale complex networks.

Key words: large-scale road network, shortest path, node importance, network partition

中图分类号: