A Simple Algorithm for Multiple-Source Shortest Paths in Planar Digraphs

Debarati Das, Evangelos Kipouridis, M. Gutenberg, Christian Wulff-Nilsen
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引用次数: 1

Abstract

Given an $n$-vertex planar embedded digraph $G$ with non-negative edge weights and a face $f$ of $G$, Klein presented a data structure with $O(n\log n)$ space and preprocessing time which can answer any query $(u,v)$ for the shortest path distance in $G$ from $u$ to $v$ or from $v$ to $u$ in $O(\log n)$ time, provided $u$ is on $f$. This data structure is a key tool in a number of state-of-the-art algorithms and data structures for planar graphs. Klein's data structure relies on dynamic trees and the persistence technique as well as a highly non-trivial interaction between primal shortest path trees and their duals. The construction of our data structure follows a completely different and in our opinion very simple divide-and-conquer approach that solely relies on Single-Source Shortest Path computations and contractions in the primal graph. Our space and preprocessing time bound is $O(n\log |f|)$ and query time is $O(\log |f|)$ which is an improvement over Klein's data structure when $f$ has small size.
平面有向图中多源最短路径的一种简单算法
给定一个$n$顶点的平面嵌入式有向图$G$,其边权为非负,面$f$为$G$, Klein给出了一个具有$O(n\log n)$空间和预处理时间的数据结构,它可以在$G$中回答$u$到$v$或$v$到$u$的最短路径距离$(u,v)$,且在$O(\log n)$时间内,假设$u$在$f$上。这种数据结构是许多最先进的算法和平面图数据结构的关键工具。Klein的数据结构依赖于动态树和持久性技术,以及原始最短路径树和它们的对偶之间高度重要的交互。我们的数据结构的构造遵循一种完全不同的,在我们看来非常简单的分而治之的方法,它完全依赖于原始图中的单源最短路径计算和收缩。我们的空间和预处理时间限制为$O(n\log |f|)$,查询时间为$O(\log |f|)$,这是对Klein的数据结构在$f$具有较小大小时的改进。
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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