The basic principle of immune algorithm based on multi-objective optimization is illustrated and in a isolation degree algorithm is rationally lead into cluster algorithm. In algorithm, the feasible solutions are regarded as antibodies and pareto optimal solution antigens preserved in an antigen population updated by a improved cluster algorithm. Then, the realization of multi-objective optimization in Matlab environment by using Immune Genetic Algorithm is discussed, especially for the algorithmic realizations of strength degree calculation, Pareto optimal solution, and hyper mutation. Finally, a practical example is made to illustrate the feasibility of the suggested algorithm in Matlab environment.