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Balanced Partitions of Trees and Applications

Authors: Feldmann, Andreas Emil; Foschini, Luca;

Balanced Partitions of Trees and Applications

Abstract

We study the k-BALANCED PARTITIONING problem in which the vertices of a graph are to be partitioned into k sets of size at most ceil(n/k) while minimising the cut size, which is the number of edges connecting vertices in different sets. The problem is well studied for general graphs, for which it cannot be approximated within any factor in polynomial time. However, little is known about restricted graph classes. We show that for trees k-BALANCED PARTITIONING remains surprisingly hard. In particular, approximating the cut size is APX-hard even if the maximum degree of the tree is constant. If instead the diameter of the tree is bounded by a constant, we show that it is NP-hard to approximate the cut size within n^c, for any constant c<1. In the face of the hardness results, we show that allowing near-balanced solutions, in which there are at most (1+eps)ceil(n/k) vertices in any of the k sets, admits a PTAS for trees. Remarkably, the computed cut size is no larger than that of an optimal balanced solution. In the final section of our paper, we harness results on embedding graph metrics into tree metrics to extend our PTAS for trees to general graphs. In addition to being conceptually simpler and easier to analyse, our scheme improves the best factor known on the cut size of near-balanced solutions from O(log^{1.5}(n)/eps^2) [Andreev and Räcke TCS 2006] to 0(log n), for weighted graphs. This also settles a question posed by Andreev and Räcke of whether an algorithm with approximation guarantees on the cut size independent from eps exists.

29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012)

Leibniz International Proceedings in Informatics (LIPIcs), 14

ISBN:978-3-939897-35-4

ISSN:1868-8969

Keywords

Bicriteria approximation, hardness of approximation, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], Balanced partitioning, balanced partitioning, 004, tree embeddings, Balanced partitioning; Bicriteria approximation; Hardness of approximation; Tree embeddings, bicriteria approximation, Data processing, computer science, Tree embeddings, [INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC], info:eu-repo/classification/ddc/004, Hardness of approximation, ddc: ddc:004

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
51
Top 10%
Top 10%
Top 10%
Green
hybrid