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论文类型：期刊论文

发表时间：2015-05-01

发表刊物：STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

收录刊物：SCIE、EI、Scopus

卷号：51

期号：5

页面范围：1051-1065

ISSN号：1615-147X

关键字：Reliability-based design optimization; Efficiency; Robustness; Chaos control

摘要：Reliability-based design optimization (RBDO) is a powerful tool for design optimization with consideration of uncertainty. It can be solved by double loop approaches or single loop approaches, while double loop approaches are robust but their implementation is computationally costly. On the other hand, single loop approaches are highly efficient but may have convergence problem for highly nonlinear performance measure functions. To mend their respective drawbacks, we resort to a transition between them and propose the so-called adaptive hybrid approach (AHA) to take advantage of these two approaches. Based on a function type criterion, AHA adaptively selects the single loop or double loop approaches during the iteration. When single loop strategy is selected, the advanced mean value (AMV) method is used. When double loop strategy is selected, an improved adaptive chaos control (ACC) method is proposed to searches for the most probable target point (MPTP) of black-box function robustly and efficiently. Four illustrative examples, including two nonlinear analytical problems and two engineering applications, demonstrate the superior efficiency and robustness of the AHA over other prevalent approaches.