Abstract: Optimization problems with uncertainties are a kind of familiar and complicated optimization problems, and most of the existing methods only deal with the case of a single-objective function. To solve multi-objective optimization problems with interval parameters by particle swarm optimization, a multi-objective particle swarm optimization algorithm based on probable dominance is proposed in this paper. In the algorithm, the probable dominance and the $\sigma$ intervals are presented to compare the quality of solutions and select the globally optimal particles, respectively. A novel strategy for updating locally optimal particles and exterior archive are put forward. The feasibility of the proposed algorithm is validated by simulation results.