GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs

TL;DR

GraphCombEx is a software tool that enables scalable exploration and analysis of combinatorial optimization problems in large complex networks, providing high-quality solutions and bounds.

Contribution

It introduces a unified, extensible framework for solving multiple combinatorial problems on large graphs with scalable heuristics and visualization capabilities.

Findings

Successfully used in recent research studies.

Supports multiple combinatorial problems.

Designed for scalability and extensibility.

Abstract

We present a prototype of a software tool for exploration of multiple combinatorial optimisation problems in large real-world and synthetic complex networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial Explorer), provides a unified framework for scalable computation and presentation of high-quality suboptimal solutions and bounds for a number of widely studied combinatorial optimisation problems. Efficient representation and applicability to large-scale graphs and complex networks are particularly considered in its design. The problems currently supported include maximum clique, graph colouring, maximum independent set, minimum vertex clique covering, minimum dominating set, as well as the longest simple cycle problem. Suboptimal solutions and intervals for optimal objective values are estimated using scalable heuristics. The tool is designed with extensibility in mind, with the view of further problems and both new fast and high-performance heuristics to be added in the future. GraphCombEx has already been successfully used as a support tool in a number of recent research studies using combinatorial optimisation to analyse complex networks, indicating its promise as a research software tool.