English

A Constant-factor Approximation for Weighted Bond Cover

Data Structures and Algorithms 2025-01-09 v2

Abstract

The Weighted F\mathcal{F}-Vertex Deletion for a class F{\cal F} of graphs asks, weighted graph GG, for a minimum weight vertex set SS such that GSF.G-S\in{\cal F}. The case when F{\cal F} is minor-closed and excludes some graph as a minor has received particular attention but a constant-factor approximation remained elusive for Weighted F\mathcal{F}-Vertex Deletion. Only three cases of minor-closed F{\cal F} are known to admit constant-factor approximations, namely Vertex Cover, Feedback Vertex Set and Diamond Hitting Set. We study the problem for the class F{\cal F} of θc\theta_c-minor-free graphs, under the equivalent setting of the Weighted cc-Bond Cover problem, and present a constant-factor approximation algorithm using the primal-dual method. For this, we leverage a structure theorem implicit in [Joret, Paul, Sau, Saurabh, and Thomass\'{e}, SIDMA'14] which states the following: any graph GG containing a θc\theta_c-minor-model either contains a large two-terminal protrusion, or contains a constant-size θc\theta_c-minor-model, or a collection of pairwise disjoint constant-sized connected sets that can be contracted simultaneously to yield a dense graph. In the first case, we tame the graph by replacing the protrusion with a special-purpose weighted gadget. For the second and third case, we provide a weighting scheme which guarantees a local approximation ratio. Besides making an important step in the quest of (dis)proving a constant-factor approximation for Weighted F\mathcal{F}-Vertex Deletion, our result may be useful as a template for algorithms for other minor-closed families.

Keywords

Cite

@article{arxiv.2105.00857,
  title  = {A Constant-factor Approximation for Weighted Bond Cover},
  author = {Eun Jung Kim and Euiwoong Lee and Dimitrios M. Thilikos},
  journal= {arXiv preprint arXiv:2105.00857},
  year   = {2025}
}

Comments

Accepted for publication to the Journal of Computer and System Sciences

R2 v1 2026-06-24T01:43:55.573Z