Abstract: A multiobjective optimization immune algorithm, based on immune response principle of the immune system and a new niche technology, is proposed to solve multiobjective optimization problems by constructing immune operators efficiently. In the algorithm, the feasible solutions are regarded as antibodies and Pareto optimal solutions antigens preserved in an antigen population updated by a new cluster algorithm. Many Pareto optimal solutions can be effectively obtained and distributed onto the Pareto front in this way. Convergence of the algorithm is proved. Finally, simulation shows that it is better than SPEA(3), which hints that multiobjective immune algorithms are a potential research area.