A dual population constrained optimization algorithm with the hybrid strategy is proposed. The method uses the dual population to deal with constrains, and employs constraint control as the approach of updating infeasible sets. The hybird strategy is used to evolve population. In the early stage of the evolution, the Deb criterion is used to generate feasible solutions, and some inferior infeasible solutions are retained to participate in the evolution to ensure the diversity of the population. In the later stage of the evolution, the global optimal solution and second-best solution take part in the evolution, so as to quickly converge. The simulation results show that, while keeping the diversity of the population, the proposed algorithm can converge to the global optimal solutions with better robustness.