Solving Graph Colouring Problems via Convex Optimization

We introduce a novel reformulation of the graph colouring problem (GCP), which is the problem of assigning labels or colours to the vertices of a graph such that no two adjacent vertices are assigned the same colour. From this we derive a convex optimization problem that finds a colouring of a given graph with the minimal possible number of colours used; an optimal colour of the graph. We aim to implement existing efficient convex optimization algorithms to this problem, identify and apply graph decomposition techniques to further improve performance, and identify what properties of a graph might make it more susceptible to this approach.

Edward Mirco

Curtin University

Edward began a BSc with a major in Physics in 2022 at Curtin University, and has participated in a scholarship research opportunity in computational quantum collision theory to be applied in international fusion energy experimental collaborations. His current research is in the field of graph theory and combinatorics, and he is to graduate at the end of 2025, and pursue postgraduate studies in pure and applied mathematics.

You may be interested in

Ben Cicchini

Ben Cicchini

Investigating the Ecological Diversity-Stability Debate using Differential Equation Models and Statistical Sampling Techniques
Geneva Birtles

Geneva Birtles

Spatial Modelling of Lesion Development Informed by Multiple Sclerosis Patient MRIs
Trillion White

Trillion White

Optimisation in BKZ: An analysis of dynamic block size
Jason Lu

Jason Lu

A Mutual Information-Based Metric for Assessing Partitions of Dynamical Systems
Contact Us

We're not around right now. But you can send us an email and we'll get back to you, asap.

Not readable? Change text.