Abstract: A multi-objective optimization genetic algorithm is proposed,which incorporates preference information of the decision maker in an interactive way.The algorithm makes use of a new ranking method based on the preference information to compare the individuals,and uses a graphical user interface to interact with the decision maker.Computational complexity of the algorithm is analyzed theoretically and simulation results indicate that the proposed algorithm can improve the searching efficiency,and can effectively find the trade-off solutions in the preferred region.Particularly,when the preference is changed,the algorithm can respond quickly to change the searching range and to find solutions in the corresponding region.