# A Dynamically Turbo-Charged Greedy Heuristic for Graph Coloring

## TL;DR

This paper presents a dynamic, turbo-charged heuristic for graph coloring that combines turbo-charging with greedy algorithms, significantly improving solution quality and efficiency through novel dynamic techniques.

## Contribution

It introduces a dynamic version of the graph coloring problem and enhances turbo-charging with new dynamic concepts like moment of regret and rollback points.

## Key findings

- The heuristic often produces exact solutions.
- It outperforms other heuristics in experiments.
- The approach is effective and efficient.

## Abstract

We introduce a dynamic version of the graph coloring problem and prove its fixed-parameter tractability with respect to the edit-parameter. This is used to present a {\em turbo-charged} heuristic for the problem that works by combining the turbo-charging technique with other standard heuristic tools, including greedy coloring. The recently introduced turbo-charging idea is further enhanced in this paper by introducing a dynamic version of the so called {\em moment of regret} and {\em rollback points}. Experiments comparing our turbo-charging algorithm to other heuristics demonstrate its effectiveness. Our algorithm often produced results that were either exact or better than all the other available heuristics.