We propose in this paper a generic algorithm based on ant colony optimization to solve multi-objective optimization problems. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. We compare different variants of this algorithm on the multi-objective knapsack problem. We compare also the obtained results with other evolutionary algorithms from the literature.