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Efficient solutions for finding vitality with respect to shortest paths

机译:在最短路径上寻找活力的有效解决方案

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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:令G =(V,E)是一个连通的,加权的,无向的图,使得| V | = n和| E | =米给定图G中源节点s和宿节点t之间的最短路径P g (s,t),无需使用特定边(或特定边缘)即可计算源宿之间的最短路径P g (s,t)中的节点)称为该边(或节点)的最短替换路径。最重要的边缘(MVE)问题是在P g (s,t)中找到一条边缘,该边缘的去除导致最长的替换最短路径。最重要节点(MVN)问题是在P G (s,t)中找到一个节点,该节点的去除会导致最长替换最短路径。在本文中,对于MVE问题,我们通过从G构造一个较小的图L G 来描述O(m + m'a(m',n'))时间算法(α表示逆阿克曼函数)我们称之为线性图,其中n'和m'分别是L G 中节点和边的数量。我们的算法还将为P g (s,t)中的每个边提出一条替代最短路径,而无需任何额外时间。对于具有整数权重的MVN问题,我们描述了O(mα(m,n))时间算法。我们的算法还将为P G (s,t)中的每个节点建议一条替换最短路径,而无需增加任何时间。

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