Abstract: Optimization design plays a very important role in the engineering applications, which often involves huge computational effort and requires powerful computing environment. However, the distributed, dynamic and heterogeneous characteristics make it more difficult to make good use of the abundant idle resources. In order to integrate the massive idle resources to super-powerful environment by resources sharing and cooperative working on Internet, a four-layer high-performance grid platform is constructed for solving the complex engineering optimization problems. The dynamic analysis program developed is sealed to the nodes of the grid as black-box for computing dynamic response. An effective optimization method using Kriging model is proposed to do dynamic optimization design of the turbine engine foundation on the grid platform. The optimization problem is to find the design variables such that both the maximum dynamic displacement and structural weight are minimum and certain side constraints are satisfied. The cross sections of the beams and columns are considered as design variables. Kriging model is used to build the approximate mapping relationship between the forced vibration amplitude and design variables, reducing expensive dynamic reanalysis. Two engineering examples are carried out successfully on the platform using the proposed method, and the computing efficiency is compared with different number grid nodes. In comparison with the result of sequential linear programming, the optimization results show that the method has good accuracy. The speed-up is also analyzed when the nodes with different number are used showing that the method has very high efficiency for grid computing, and the grid platform constructed is suitable for the engineering optimization design.