A Hybrid Artificial Bee Colony Algorithm for Graph 3-Coloring
This is an incremental improvement for researchers and practitioners in optimization, addressing a specific discrete optimization problem.
The paper tackled the graph 3-coloring problem by proposing a hybrid Artificial Bee Colony (HABC) algorithm, which matched the results of top algorithms like Tabucol and HEA and outperformed EA-SAW on certain graph types.
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.