An efficient constraint boundary sampling method for sequential RBDO using kriging surrogate model

Abstract

Reliability-based design optimization (RBDO) requires a high computational cost owing to its reliability analysis. A surrogate model is introduced to reduce the computational cost in RBDO. The accuracy of the reliability depends on the accuracy of the surrogate model of constraint boundaries in the surrogated-model-based RBDO. In earlier researches, constraint boundary sampling (CBS) was proposed to approximate accurately the boundaries of constraints by locating sample points on the boundaries of constraints. However, because CBS uses sample points on all constraint boundaries, it creates superfluous sample points. In this paper, efficient constraint boundary sampling (ECBS) is proposed to enhance the efficiency of CBS. ECBS uses the statistical information of a kriging surrogate model to locate sample points on or near the RBDO solution. The efficiency of ECBS is verified by mathematical examples. ？ 2016 The Korean Society of Mechanical Engineers.