Fixed-parameter algorithms for the weighted max-cut problem on embedded 1-planar graphs

Fixed-parameter algorithms for the weighted max-cut problem on embedded 1-planar graphs

Abstract

We propose two fixed-parameter tractable algorithms for the weighted Max-Cut problem on embedded 1-planar graphs parameterized by the crossing number k of the given embedding. A graph is called 1-planar if it can be drawn in the plane with at most one crossing per edge. Our algorithms recursively reduce a 1-planar graph to at most planar graphs, using edge removal and node contraction. Our main algorithm then solves the Max-Cut problem for the planar graphs using the FCE-MaxCut introduced by Liers and Pardella [23]. In the case of non-negative edge weights, we suggest a variant that allows to solve the planar instances with any planar Max-Cut algorithm. We show that a maximum cut in the given 1-planar graph can be derived from the solutions for the planar graphs. Our algorithms compute a maximum cut in an embedded weighted 1-planar graph with n nodes and k edge crossings in time .

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Authors
  • Dahn, Christine
  • Kriege, Nils M.
  • Mutzel, Petra
  • Schilling, Julian
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Shortfacts
Category
Journal Paper
Divisions
Data Mining and Machine Learning
Subjects
Theoretische Informatik
Journal or Publication Title
Theoretical Computer Science
ISSN
0304-3975
Publisher
Elsevier
Page Range
pp. 172-184
Volume
852
Date
January 2021
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