In this paper, an adaptive membrane evolutionary algorithm (AMEA) is proposed, which combines a dynamic membrane structure and a differential evolution with the adaptive mutation factor. In the AMEA, the feasibility proportion method is used to dynamically adjust the size of the elementary membrane in the optimization process. The results of the experimental indicate that the proposed algorithm outperforms other evolutionary algorithms on five well-known constrained engineering optimization problems.