Approximation algorithms for connected maximum cut and related problems

Mohammad Taghi Hajiaghayi, Guy Kortsarz, Robert MacDavid, Manish Purohit, Kanthi Sarpatwar

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

An instance of the Connected Maximum Cut problem consists of an undirected graph G=(V,E) and the goal is to find a subset of vertices S⊆V that maximizes the number of edges in the cut δ(S) such that the induced graph G[S] is connected. We present the first non-trivial Ω([Formula presented]) approximation algorithm for the Connected Maximum Cut problem in general graphs using novel techniques. We then extend our algorithm to edge weighted case and obtain a poly-logarithmic approximation algorithm. Interestingly, in contrast to the classical Max-Cut problem that can be solved in polynomial time on planar graphs, we show that the Connected Maximum Cut problem remains NP-hard on unweighted, planar graphs. On the positive side, we obtain a polynomial time approximation scheme for the Connected Maximum Cut problem on planar graphs and more generally on bounded genus graphs.

Original languageEnglish (US)
Pages (from-to)74-85
Number of pages12
JournalTheoretical Computer Science
Volume814
DOIs
StatePublished - Apr 24 2020

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Approximation algorithms
  • Connected maximum cut
  • Connected submodular maximization

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