A Hybrid Artificial Bee Colony Algorithm for Graph 3-Coloring

TL;DR

This paper introduces a hybrid Artificial Bee Colony algorithm for graph 3-coloring, demonstrating competitive performance and improvements over traditional heuristics on various graph types.

Contribution

The paper presents a novel hybrid ABC algorithm specifically designed for graph 3-coloring, outperforming traditional heuristics on several graph categories.

Findings

HABC matches state-of-the-art algorithms in performance.

HABC outperforms EA-SAW on medium-sized graphs.

Extensive experiments validate the effectiveness of HABC.

Abstract

The Artificial Bee Colony (ABC) is the name of an optimization algorithm that was inspired by the intelligent behavior of a honey bee swarm. It is widely recognized as a quick, reliable, and efficient methods for solving optimization problems. This paper proposes a hybrid ABC (HABC) algorithm for graph 3-coloring, which is a well-known discrete optimization problem. The results of HABC are compared with results of the well-known graph coloring algorithms of today, i.e. the Tabucol and Hybrid Evolutionary algorithm (HEA) and results of the traditional evolutionary algorithm with SAW method (EA-SAW). Extensive experimentations has shown that the HABC matched the competitive results of the best graph coloring algorithms, and did better than the traditional heuristics EA-SAW when solving equi-partite, flat, and random generated medium-sized graphs.