Losing Treewidth In The Presence Of Weights
Michał Włodarczyk
TL;DR
The presented algorithm is based on a novel technique of random sampling of so-called protrusions and admits a randomized polynomial-time constant-factor approximation algorithm for every fixed $\eta$.
Abstract
In the Weighted Treewidth-$η$ Deletion problem we are given a node-weighted graph $G$ and we look for a vertex subset $X$ of minimum weight such that the treewidth of $G-X$ is at most $η$. We show that Weighted Treewidth-$η$ Deletion admits a randomized polynomial-time constant-factor approximation algorithm for every fixed $η$. Our algorithm also works for the more general Weighted Planar $F$-M-Deletion problem. This work extends the results for unweighted graphs by [Fomin, Lokshtanov, Misra, Saurabh; FOCS '12] and answers a question posed by [Agrawal, Lokshtanov, Misra, Saurabh, Zehavi; APPROX/RANDOM '18] and [Kim, Lee, Thilikos; APPROX/RANDOM '21]. The presented algorithm is based on a novel technique of random sampling of so-called protrusions.
