Efficient Branch-and-Bound Algorithms for Finding Triangle-Constrained 2-Clubs

TL;DR

This paper introduces efficient branch-and-bound algorithms with data reduction for the Vertex Triangle 2-Club problem, significantly improving solution times on large sparse graphs and extending to edge-based triangle constraints.

Contribution

It presents a novel combinatorial branch-and-bound approach with data reduction rules for the Vertex Triangle 2-Club problem, outperforming previous ILP-based methods.

Findings

Outperforms existing ILP-based algorithms on large sparse graphs

Can find optimal solutions in minutes for graphs with over 100,000 vertices

Extends to Edge Triangle 2-Club problem with similar efficiency

Abstract

In the Vertex Triangle 2-Club problem, we are given an undirected graph $G$ and aim to find a maximum-vertex subgraph of $G$ that has diameter at most 2 and in which every vertex is contained in at least $\ell$ triangles in the subgraph. So far, the only algorithm for solving Vertex Triangle 2-Club relies on an ILP formulation [Almeida and Br\'as, Comput. Oper. Res. 2019]. In this work, we develop a combinatorial branch-and-bound algorithm that, coupled with a set of data reduction rules, outperforms the existing implementation and is able to find optimal solutions on sparse real-world graphs with more than 100,000 vertices in a few minutes. We also extend our algorithm to the Edge Triangle 2-Club problem where the triangle constraint is imposed on all edges of the subgraph.