Heuristic information for ant colony optimization for the feature selection problem

The use of heuristic information is crucial for good performance of ant colony optimization (ACO) algorithms. The use of heuristic information can guide the artificial ants towards the most promising solutions. Feature selection problems are different from many other optimisation problems that have been solved using ACO algorithms in that they do not have heuristic information that can be used in guiding the search process besides the pheromone values. This study aims to try different heuristic information that can be used in guiding the search process besides the pheromone values. The results showed using different heuristic information in guiding the search process besides the pheromone values. The last heuristic is best-suited to support the feature selection task.