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Nonuniform Graph Partitioning with Unrelated Weights

机译:具有不相关权重的非均匀图分区

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We give a bi-criteria approximation algorithm for the Minimum Nonuniform Partitioning problem, recently introduced by Krauthgamer, Naor, Schwartz and Talwar (2014). In this problem, we are given a graph G = (V, E) on n vertices and k numbers ρ_1,...,ρ_k. The goal is to partition the graph into k disjoint sets P_1,..., P_k satisfying |P_i| ≤ ρ_in so as to minimize the number of edges cut by the partition. Our algorithm has an approximation ratio of O((log n log k)~(1/2)) for general graphs, and an O(1) approximation for graphs with excluded minors. This is an improvement upon the O(log n) algorithm of Krauthgamer, Naor, Schwartz and Talwar (2014). Our approximation ratio matches the best known ratio for the Minimum (Uniform) k-Partitioning problem. We extend our results to the case of "unrelated weights" and to the case of "unrelated d-dimensional weights". In the former case, different vertices may have different weights and the weight of a vertex may depend on the set P_i the vertex is assigned to. In the latter case, each vertex u has a d-dimensional weight r(u,i) = (r_1(u,i),..., r_d(u, i)) if u is assigned to P_i. Each set P_i has a d-dimensional capacity c(i) = (c_1(i),... ,C_d(i)). The goal is to find a partition such that Σ_(u∈P_i) r(u,i) ≤ c(i) coordinate-wise.
机译:我们给出了最小不均匀分区问题的双准则逼近算法,该算法最近由Krauthgamer,Naor,Schwartz和Talwar(2014)引入。在这个问题中,我们在n个顶点和k个数字ρ_1,...,ρ_k上得到了G =(V,E)的图。目标是将图划分为满足| P_i |的k个不相交的集合P_1,...,P_k。 ≤ρ_in,以最大程度地减少隔板切割出的边的数量。对于一般图,我们的算法的逼近度为O((log n log k)〜(1/2)),对于排除了未成年人的图,其算法的逼近度为O(1)。这是对Krauthgamer,Naor,Schwartz和Talwar(2014)的O(log n)算法的改进。我们的近似比率与最小(均匀)k分区问题的最佳比率相匹配。我们将结果扩展到“不相关权重”的情况和“不相关d维权重”的情况。在前一种情况下,不同的顶点可能具有不同的权重,并且顶点的权重可能取决于顶点分配给的集合P_i。在后一种情况下,如果将u分配给P_i,则每个顶点u的d维权重r(u,i)=(r_1(u,i),...,r_d(u,i))。每个集合P_i具有d维容量c(i)=(c_1(i),...,C_d(i))。目的是找到一个分区,使得Σ_(u∈P_i)r(u,i)≤c(i)逐个坐标。

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