A multi-objective disturbance biogeography-based optimization algorithm(MDBBO) is proposed for multiobjective optimization problems(MOPs). Based on the ratio of non-dominated feasible solutions in current population, individuals are evaluated by combining their non-dominated rank sorting and crowded distances. A disturbance migration operator is proposed based on the biogeography migration strategy, which is applied to the evolution of the population so that the diversity of the population can be improved. An archive population is applied to store non-dominated feasible individuals gained, while the method of circle crowded disturbance is used to update the archive population to ensure the uniform distribution of population. Simulation results on benchmark test problems show the effectiveness of the MDBBO for MOPs.