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In this article we present an application of the Ant Colony Optimization (ACO) metaheuristic to the single machine total weighted tardiness problem. First, we briefly discuss the constructive phase of ACO in which a colony of artificial ants generates a set of feasible solutions. Then, we introduce some simple but very effective local search. Last, we combine the constructive phase with local search obtaining a novel ACO algorithm that uses a heterogeneous colony of ants and is highly effective in finding the best-known solutions on all instances of a widely used set of benchmark problems.