Stubborn ants

In ant colony optimization methods, including ant system and max-min ant system, each ant stochastically generates its candidate solution, in a given iteration, based on the same pheromone tau and heuristic eta information as every other ant. In this paper, we propose a variation in which if an ant generates a particular candidate solution S t-1 in iteration t - 1, then the solution components of S t-1 will have a higher probability of being selected in the candidate solution S t generated by that ant in iteration t. In other words, each ant will be biased in favor of its past decisions, i.e. it will be stubborn. We evaluate this variation in the context of max-min ant system and the traveling salesman problem (TSP), using different degrees of stubbornness, and applying the ANOVA test of statistical significance to determine the level of significance of the results.