AN ALGORITHM FOR SOLVING GRAPH COLORING PROBLEMS BASED ON AN IMPROVED ANT COLONY OPTIMIZATION

The Graph Coloring Problem (GCP) is a significant research area in graph theory, and new breakthroughs are constantly being made, while the ant colony optimization shows its outstanding ability to solve path planning problems. In this research, the ant colony optimization method is made full use of to improve it using one kind of greedy algorithm, and the effectiveness of this proposed solution algorithm for the coloring problem in a realistic directed and undirected network environment is validated. It is demonstrated that the proposed GAC-GC graph coloring solution method has better efficiency and accuracy than the classical algorithm for coloring problems. In future research, further improvements can be made from various perspectives, such as application scenarios, integrated application of algorithmic data pre-processing, and hybrid algorithm improvement.