A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were proposed in the literature. These extensions typically achieve much improved computational results when compared to the original Ant System. However, many design choices of Ant System are left untouched including the fact that solutions are constructed, that real-numbers are used to simulate pheromone trails, and that explicit pheromone evaporation is used. In this article we experimentally investigate adaptations of ant algorithms to the traveling salesman problem that use alternative choices for these latter features: we consider using pheromones to modify solutions and different schemes for manipulating pheromone trails based on integer pheromone trails without recurring to pheromone evaporation.