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Efficient solutions for finding vitality with respect to shortest paths

机译:关于最短路径寻找生命力的高效解决方案

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Let G = (V, E) be a connected, weighted, undirected graph such that |V| = n and |E| = m. Given a shortest path Pg (s, t) between a source node s and a sink node t in the graph G, computing the shortest path between source and sink without using a particular edge (or a particular node) in Pg(s, t) is called Replacement Shortest Path for that edge (or node). The Most Vital Edge (MVE) problem is to find an edge in Pg(s, t) whose removal results in the longest replacement shortest path. And the Most Vital Node (MVN) problem is to find a node in PG(s, t) whose removal results in the longest replacement shortest path. In this paper for the MVE problem we describe an O(m+m'a(m', n')) time algorithm (α represents Inverse Ackermann function) by constructing a smaller graph LG from G which we call Linear Graph, where n' and m' are the number of nodes and edges in LG respectively. Our algorithm will also suggest a replacement shortest path for every edge in Pg(s, t) without any additional time. For the MVN problem, with integer weights, we describe an O(mα(m, n)) time algorithm. Our algorithm will also suggest a replacement shortest path for every node in PG (s, t) without any additional time.
机译:设g =(v,e)是连接的加权,无向图,这样V | = n和| e | = m。授予图表G中的宿节点T之间的最短路径P G (s,t),计算源极短路和托管之间的最短路径而不使用特定边缘(或特定的节点)在P G (S,T)中称为该边缘(或节点)的替换最短路径。最重要的边缘(MVE)问题是在P G (S,T)中找到一个边缘,其删除导致最长的更换最短路径。并且最重要的节点(MVN)问题是在P G (s,t)中找到一个节点,其删除导致最长的更换最短路径。在本文中,MVE问题我们描述了O(M + M'a(M',N'))时间算法(α代表逆Ackermann函数)通过​​构造G G FROM G.我们呼叫线性图形,其中n'和m'是分别的L G 中的节点和边的数量。我们的算法还将为P G (S,T)中的每个边缘的替代最短路径没有任何额外的时间。对于MVN问题,通过整数重量,我们描述了一个(Mα(M,N))时间算法。我们的算法还将为P G (S,T)中的每个节点没有任何额外时间的替代最短路径。

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