Abstract
The second-order reliability method (SORM) is an effective tool to evaluate the reliability, but its application for reliability-based design optimization faces unbearable computational cost. In this study, a new hybrid sequential approximate programming (HSAP) method is developed to calculate the optimum efficiently by developing a distance-checking criterion and a convex approximate method. Since the distance-checking criterion identifies the feasibility of the probabilistic constraint effectively, the proposed method combines the efficiency of the sequential approximate programming method and the accuracy of SORM. The convex approximate method is also constructed using the sensitivity and function value of the probabilistic constraint. So no additional computational cost is required in the optimization process. Five illustrative examples, including two mathematical examples and thee practical engineering examples, demonstrate the efficiency and accuracy of the proposed HSAP.
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