A method combined ant colony algorithm with particle swarm optimization algorithm was designed for solving multi-objective flexible job shop scheduling problem in this paper. In the combined algorithm the start position of ants was marked by particles optimum position obtained by particle swarm optimization algorithm. Then the traditional ant colony algorithm was improved and was used to search the global optimum scheduling. The combined algorithm was validated by practical instances. The results obtained have shown the proposed approach is feasible and effective for the multi-objective flexible job shop scheduling problem.