A simple $(2+\epsilon)$-approximation algorithm for Split Vertex Deletion

TL;DR

This paper presents a straightforward deterministic algorithm that achieves a near-optimal approximation ratio for the Split Vertex Deletion problem, improving simplicity while maintaining performance.

Contribution

It introduces an extremely simple deterministic $(2+oldsymbol{ ext{epsilon}})$-approximation algorithm for SVD, advancing prior randomized approaches.

Findings

Achieves a $(2+oldsymbol{ ext{epsilon}})$-approximation deterministically.

Simplifies previous algorithms for SVD.

Maintains near-optimal approximation ratio under complexity assumptions.

Abstract

A split graph is a graph whose vertex set can be partitioned into a clique and a stable set. Given a graph $G$ and weight function $w: V(G) \to \mathbb{Q}_{\geq 0}$, the Split Vertex Deletion (SVD) problem asks to find a minimum weight set of vertices $X$ such that $G-X$ is a split graph. It is easy to show that a graph is a split graph if and only it it does not contain a $4$-cycle, $5$-cycle, or a two edge matching as an induced subgraph. Therefore, SVD admits an easy $5$-approximation algorithm. On the other hand, for every $\delta >0$, SVD does not admit a $(2-\delta)$-approximation algorithm, unless P=NP or the Unique Games Conjecture fails. For every $\epsilon >0$, Lokshtanov, Misra, Panolan, Philip, and Saurabh recently gave a randomized $(2+\epsilon)$-approximation algorithm for SVD. In this work we give an extremely simple deterministic $(2+\epsilon)$-approximation algorithm for SVD.