English

On Approximating Cutwidth and Pathwidth

Data Structures and Algorithms 2024-04-15 v2

Abstract

We study graph ordering problems with a min-max objective. A classical problem of this type is cutwidth, where given a graph we want to order its vertices such that the number of edges crossing any point is minimized. We give a log1+o(1)(n) \log^{1+o(1)}(n) approximation for the problem, substantially improving upon the previous poly-logarithmic guarantees based on the standard recursive balanced partitioning approach of Leighton and Rao (FOCS'88). Our key idea is a new metric decomposition procedure that is suitable for handling min-max objectives, which could be of independent interest. We also use this to show other results, including an improved log1+o(1)(n) \log^{1+o(1)}(n) approximation for computing the pathwidth of a graph.

Keywords

Cite

@article{arxiv.2311.15639,
  title  = {On Approximating Cutwidth and Pathwidth},
  author = {Nikhil Bansal and Dor Katzelnick and Roy Schwartz},
  journal= {arXiv preprint arXiv:2311.15639},
  year   = {2024}
}