A new algorithm for constrained multi-objective optimization is presented.The algorithm treats the constraints as an objective and the immune clone and immune memory mechanism are introduced.Therefore

the new algorithm could find the Pareto-optimal solutions from the feasible region and the edge of the infeasible region

which assures both the convergence and diversity of the obtained solutions.Simulation results show that the new algorithm has much better performance in finding a much better spread of solutions

in maintaining a better uniformity of the solutions and in obtaining a better convergence.