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k-Edge-Connectivity: Approximation and LP Relaxation

机译:K-Edge-Connectivity:近似和LP松弛

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In the k-edge-connected spanning subgraph problem we are given a graph (V, E) and costs for each edge, and want to find a minimum-cost F C E such that (V, F) is k-edge-connected. We show there is a constant ε > 0 so that for all k > 1, finding a (1 + ε)-approximation for k-ECSS is NP-hard, establishing a gap between the unit-cost and general-cost versions. Next, we consider the multi-subgraph cousin of k-ECSS, in which we purchase a multi-subset F of E, with unlimited parallel copies available at the same cost as the original edge. We conjecture that a (1 + Θ(1/k))-approximation algorithm exists, and we describe an approach based on graph decompositions applied to its natural linear programming (LP) relaxation. The LP is essentially equivalent to the Held-Karp LP for TSP and the undirected LP for Steiner tree. We give a family of extreme points for the LP which are more complex than those previously known.
机译:在K-Edge连接的跨越子图问题中,我们被给出了每个边缘的图(V,e)和成本,并且希望找到最小成本f c e,使得(v,f)是k边缘连接的。我们显示出常数ε> 0,使所有k> 1为此,找到(1±ε) - K-ECS的千克硬质,在单位成本和一般成本版本之间建立间隙。接下来,我们考虑K-ECS的多子图表姐,其中我们购买了一个多子集F的e,以与原始边缘相同的成本可用的无限制并行副本。我们猜测(1 +θ(1 / k)) - 近似算法存在,并且我们描述了一种基于曲线图分解的方法,其应用于其自然线性编程(LP)松弛。 LP基本上相当于持有的KARP LP,用于TSP和施蒂纳树的无向LP。我们为LP提供了一个极端点的一个极端点,这些都比先前已知的LP更复杂。

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