# Exploiting Reduction Rules and Data Structures: Local Search for Minimum Vertex Cover in Massive Graphs

arXiv: https://arxiv.org/abs/1509.05870 · HTML: https://mlsanity.com/paper/1509.05870/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2015.

## Built on by (most cited first, 1 of 1)

- [GRALS: GCN-Guided Redundancy-Aware Local Search for Minimum Vertex Cover](https://mlsanity.com/paper/2503.06396/) (2025)

## Abstract (arXiv)

The Minimum Vertex Cover (MinVC) problem is a well-known NP-hard problem. Recently there has been great interest in solving this problem on real-world massive graphs. For such graphs, local search is a promising approach to finding optimal or near-optimal solutions. In this paper we propose a local search algorithm that exploits reduction rules and data structures to solve the MinVC problem in such graphs. Experimental results on a wide range of real-word massive graphs show that our algorithm finds better covers than state-of-the-art local search algorithms for MinVC. Also we present interesting results about the complexities of some well-known heuristics.