On Approximating Cutwidth and Pathwidth
November 27, 2023 Β· Declared Dead Β· π IEEE Annual Symposium on Foundations of Computer Science
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Authors
Nikhil Bansal, Dor Katzelnick, Roy Schwartz
arXiv ID
2311.15639
Category
cs.DS: Data Structures & Algorithms
Citations
2
Venue
IEEE Annual Symposium on Foundations of Computer Science
Last Checked
4 months ago
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 $ \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 $ \log^{1+o(1)}(n)$ approximation for computing the pathwidth of a graph.
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