All pairs shortest paths in weighted directed graphs-exact and almost exact algorithms

Uri Zwick
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引用次数: 98

Abstract

We present two new algorithms for solving the All Pairs Shortest Paths (APSP) problem for weighted directed graphs. Both algorithms use fast matrix multiplication algorithms. The first algorithm solves the APSP problem for weighted directed graphs in which the edge weights are integers of small absolute value in O/spl tilde/(n/sup 2+/spl mu//) time, where /spl mu/ satisfies the equation /spl omega/(1,/spl mu/,1)=1+2/spl mu/ and /spl omega/(1,/spl mu/,1) is the exponent of the multiplication of an n/spl times/n/sup /spl mu// matrix by an n/sup /spl mu///spl times/n matrix. The currently best available bounds on /spl omega/(1,/spl mu/,1), obtained by Coppersmith and Winograd, and by Huang and Pan, imply that /spl mu/<0.575. The running time of our algorithm is therefore O(n/sup 2.575/). Our algorithm improves on the O/spl tilde/(n/sup (3+/spl omega/)/2/) time algorithm, where /spl omega/=/spl omega/(1,1,1)<2.376 is the usual exponent of matrix multiplication, obtained by Alon, Galil and Margalit, whose running time is only known to be O(n/sup 2.688/). The second algorithm solves the APSP problem almost exactly for directed graphs with arbitrary non-negative real weights. The algorithm runs in O/spl tilde/((n/sup /spl omega////spl epsiv/)/spl middot/log(W//spl epsiv/)) time, where /spl epsiv/>0 is an error parameter and W is the largest edge weight in the graph, after the edge weights are scaled so that the smallest non-zero edge weight in the graph is 1. It returns estimates of all the distances in the graph with a stretch of at most 1+/spl epsiv/. Corresponding paths can also be found efficiently.
加权有向图中的所有对最短路径——精确和几乎精确算法
提出了求解加权有向图的全对最短路径问题的两种新算法。两种算法都使用快速矩阵乘法算法。第一种算法解决了在0 /spl波浪/(n/sup 2+/spl mu//)时间内边权为小绝对值整数的加权有向图的APSP问题,其中/spl mu/满足方程/spl ω /(1,/spl mu/,1)=1+2/spl mu/和/spl ω /(1,/spl mu/,1)是n/spl乘以/n/sup /spl mu///spl乘以/n矩阵的指数。Coppersmith和Winograd以及Huang和Pan获得的/spl ω /(1,/spl mu/,1)上的当前最佳可用边界意味着/spl mu/0是一个误差参数,W是图中最大的边权,在对边权进行缩放使图中最小的非零边权为1之后。它返回图中所有距离的估计值,其最长长度为1+/spl / epsiv/。也可以有效地找到相应的路径。
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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