A new constraint-handling technique based on Pareto-optimality concept is proposed for evolutionary algorithms to efficiently deal with multiobjective multi-constraint design optimization problems. The essence of the proposed method is to apply non-dominance concept based on constraint function values to infeasible designs and to apply nondominance concept based on objective function values to feasible designs. The proposed technique does not need any constants to be tuned as the proposed technique does not use weighted-sum of constraints. First, the proposed approach is demonstrated to be remarkably more robust than traditional constraint-handling techniques through the optimal design of a welded beam and conceptual design optimization of a two-stage-to-orbit space plane. Next, high-fidelity aerodynamic design optimization of an axial compressor blade design is demonstrated.