Ant colony optimization (ACO)‎ for graph coloring problem

Abstract EN

We describe an artificial Ant Colony Optimization (ACO) capable of solving the graph coloring problem.

Ants of the artificial colony are able to generate successively shorter feasible tours by using information accumulated in the form of pheromone trail deposited of the edge of the colonies ant.

Computer simulations demonstrate that the artificial ant colony is capable of generating good solutions.

It is the successful use natural metaphor to design an optimization algorithm.

We generated randomly 20 graphs of 100 nodes, the performance is a best than any other available heuristic techniques such that genetic algorithm and others, so the average of coloring of a graphs is less than any other algorithms.

We achieve the goal the goal of the problem.