Abstract: A multi-objective optimization method based on model management framework is suggested to improve the efficiency and decrease the error of the approximate model for the computation-intensive engineering problem. The approximate model is built by extended radial basis functions, and then the non-dominated solutions predicted by the approximate model are identified through the micro multi-objective genetic algorithm. Then, the management framework updates the approximate model and controls the iteration time and the error resulting from the approximate model. Finally, the non-dominated solutions whose errors are controlled appropriately can be regarded as solutions to the problem. The proposed method is successfully applied to the analysis of thin-walled sections for structural crashworthiness, demonstrating that it can solve complex computation- intensive engineering multi-objective optimization problem.