Parameterized Algorithms for Graph Partitioning Problems

Hadas Shachnai, Meirav Zehavi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We study a broad class of graph partitioning problems. Each problem is defined by two constants, α1 and α2. The input is a graph G, an integer k and a number p, and the objective is to find a subset U⊆ V of size k, such that α1m1 + α2m2 is at most (or at least) p, where m1, m2 are the cardinalities of the edge sets having both endpoints, and exactly one endpoint, in U, respectively. This class of fixed-cardinality graph partitioning problems (FGPPs) encompasses Max (k, n − k)-Cut, Mink-Vertex Cover, k-Densest Subgraph, and k-Sparsest Subgraph. Our main result is a 4k + o(k)Δk⋅nO(1) time algorithm for any problem in this class, where Δ ≥ 1 is the maximum degree in the input graph. This resolves an open question posed by Bonnet et al. (Proc. International Symposium on Parameterized and Exact Computation, 2013). We obtain faster algorithms for certain subclasses of FGPPs, parameterized by p, or by (k + p). In particular, we give a 4p + o(p)⋅nO(1) time algorithm for Max (k, n − k)-Cut, thus improving significantly the best known pp⋅nO(1) time algorithm by Bonnet et al.

Original languageEnglish
Pages (from-to)721-738
Number of pages18
JournalTheory of Computing Systems
Volume61
Issue number3
DOIs
StatePublished - 1 Oct 2017
Externally publishedYes

Keywords

  • Graph partitioning
  • Parameterized algorithm
  • Random separation
  • Representative family

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