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Partitioning the Nodes of a Graph to Minimize the Sum of Subgraph Radii

机译:划分图的节点以最小化子图半径的总和

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Let G = (V, E) denote a weighted graph of n nodes and m edges, and let G[V'] denote the subgraph of G induced by a subset of nodes V' is contained in V. The radius of G[V'] is the maximum length of a shortest path in G[V'] emanating from its center (i.e., a node of G[V'] of minimum eccentricity). In this paper, we focus on the problem of partitioning the nodes of G into exactly p non-empty subsets, so as to minimize the sum of the induced subgraph radii. We show that this problem - which is of significance in facility location applications - is NP-hard when p is part of the input, but for a fixed constant p > 2 it can be solved in O(n~(2p)/p!) time. Moreover, for the notable case p = 2, we present an efficient O(mn~2 + n~3 log n) time algorithm.
机译:令G =(V,E)表示n个节点和m个边的加权图,并且让G [V']表示由节点V'的子集引起的G的子图。 ']是从G [V']的中心(即最小偏心距G [V']的节点)发出的最短路径的最大长度。在本文中,我们关注于将G的节点精确地划分为p个非空子集的问题,以最大程度地减少子图半径的和。我们表明,当p是输入的一部分时,这个问题-在设施定位应用中很重要-是NP难的,但是对于固定常数p> 2,它可以解决O(n〜(2p)/ p! ) 时间。此外,对于明显的情况p = 2,我们提出了一种有效的O(mn〜2 + n〜3 log n)时间算法。

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