We propose in this paper a generic algorithm based on Ant Colony Optimization metaheuristic (ACO) to solve multi-objective optimization problems (PMO). 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.