Large-Scale Distance Matrix Calculation Method Based on Contraction Hierarchies

Weijun Wang, Haixia Pan, Yefan Cao
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Abstract

With the rapid development and popularization of mobile positioning devices such as mobile phones, location-based services play an increasingly important role in people’s production and life, which makes high-performance large-scale distance matrix calculation a key part of the optimization of many business scenarios. The distance matrix is used to calculate the shortest road distance of a group of starting and ending points in batches. Based on the Contraction Hierarchies algorithm, this paper proposes a method to quickly calculate the distance matrix between source nodes s and target nodes t, where the source nodes s $\in$ S and target nodes t $\in$ T. Under the scale of the road network in mainland China, take $|\mathrm{S}|=|\mathbf{T}|=10000$, the average solution time of the algorithm is only 7.2 minutes, which can meet the needs of various application scenarios.
基于收缩层次的大规模距离矩阵计算方法
随着手机等移动定位设备的快速发展和普及,基于位置的服务在人们的生产和生活中发挥着越来越重要的作用,这使得高性能的大规模距离矩阵计算成为许多业务场景优化的关键部分。距离矩阵用于批量计算一组起点和终点的最短道路距离。本文基于收缩层次算法,提出了一种快速计算源节点s与目标节点t之间距离矩阵的方法,其中源节点s $\in$ s,目标节点t $\in$ t。在中国大陆道路网络规模下,取$|\ mathm {s}|=|\mathbf{t}|=10000$,算法的平均求解时间仅为7.2分钟,可以满足各种应用场景的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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