Multiobjective reliability-based optimization for design of a vehicledoor

Structural optimization for vehicle door signifies one of the key topics of research to continuously improve its performances. However, majority of the studies to date have not considered uncertainties whilst it has been known that a deterministic optimization may lead to an unreliable design in practice. In this paper, a multiobjective reliability-based design optimization (MORBDO) procedure is proposed to explore the design of vehicle door. To improve the efficiency of optimization, response surface method (RSM) is used to replace the time-consuming finite element simulations. In conjunction with Monte Carlo simulation and descriptive sampling technique, probabilistic sufficiency factor is adopted as a design constraint. The multiobjective particle swarm optimization (MOPSO) algorithm is employed to perform the optimization. The results demonstrate that the proposed optimization procedure is capable of generating a well-distributed Pareto frontier of reliable solutions, and it is suggested to select an optimum from relative insensitive regions. Moreover, the influence of varying the uncertainty and increasing the target reliability level in the optimization results is analyzed, which provided decision-makers with insightful design information.