A center differential evolution algorithm with adaptive crossover factor for constrained optimization modified differential evolution algorithm (ACFCDE) was proposed to solve constraint optimization problems. The algorithm used three simple selection criteria based on feasibility to guide the search in the feasible region. The proposed algorithm did not adopt the penalty function method, in contrast to the penalty function method, the constraint-handing technique of this algorithm was very simple, it did not require additional parameters. In addition, the center point of the population was incorporated into the DE algorithm, which only participated in the competition of the best point with the other individuals of the population, did not in any differential evolutions. And the crossover factor of DE algorithm dynamically and linearly was modified. As these measures were adopted, the stability, robustness and global searching performance of DE algorithm have been improved greatly. Results of simulations and comparisons with the other algorithms based on four testing functions demonstrated the effectiveness, efficiency and robustness of the proposed ACFCDE.