The Set Covering Problem (SCP) is a well-known NP hard discrete optimization problem that has been applied to a wide range of industrial applications, including those involving scheduling, production planning and location problems. The main difficulties when solving the SCP with a metaheuristic approach are the solution infeasibility and set redundancy. In this paper we evaluate a state of the art new formulation of the SCP which eliminates the need to address the infeasibility and set redundancy issues. The experimental results, conducted on a portfolio of SCPs from the Beasley’s OR-Library, show the gains obtained when using a new formulation to solve the SCP using the ACO metaheuristic.