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A faster algorithm for the inverse spanning tree problem

机译:逆生成树问题的更快算法

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In this paper, we consider the inverse spanning tree problem. Given an undirected graph G(0) = (N-0, A(0)) with n nodes, m arcs, an are cost vector c, and a spanning tree T-0, the inverse spanning tree problem is to perturb the are cost vector c to a vector d so that T-0 is a minimum spanning tree with respect to the cost vector d and the cost of perturbation given by d - c = Sigma((i,j)epsilon) (A)d(ij) - c(ij) is minimum. We show that the dual of the inverse spanning tree problem is a bipartite node weighted matching problem on a specially structured graph (which we call the path graph) that contains m nodes and as many as (m - n + 1)(n - 1) = O(nm) arcs. We first transform the bipartite node weighted matching problem into a specially structured minimum cost flow problem and use its special structure to develop an O(n(3)) algorithm. We next use its special structure more effectively and develop an O(n(2)log n) time algorithm. This improves the previous O(n(3)) time algorithm due to Sokkalingam et al. (1999, Oper. Res. 47, 291-298). (C) 2000 Academic Press. [References: 18]
机译:在本文中,我们考虑了逆生成树问题。给定一个无向图G(0)=(N-0,A(0)),其中有n个节点,m个圆弧,一个成本向量c和一个生成树T-0,则反向生成树问题是扰动区域将成本向量c转换为向量d,以使T-0是成本向量d和 d-c = Sigma((i,j)epsilon)(A)给出的摄动成本的最小生成树d(ij)-c(ij)为最小值。我们证明了逆生成树问题的对偶是包含m个节点且多达(m-n + 1)(n-1)个特殊结构图(我们称为路径图)上的二分节点加权匹配问题)= O(nm)弧。我们首先将二元节点加权匹配问题转换为特殊结构的最小成本流问题,并使用其特殊结构来开发O(n(3))算法。接下来,我们将更有效地使用其特殊结构,并开发O(n(2)log n)时间算法。由于Sokkalingam等人,这改进了以前的O(n(3))时间算法。 (1999,Oper.Res.47,291-298)。 (C)2000学术出版社。 [参考:18]

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