论文标题
S-BORM：使用缓冲优化和可靠性方法对通用系统的可靠性优化
S-BORM: Reliability-based optimization of general systems using buffered optimization and reliability method
论文作者
论文摘要
基于可靠性的优化（RBO）对于确定设计和操作工程系统的最佳风险建议决策至关重要。但是，它的计算仍然具有挑战性，因为它需要同时进行优化和可靠性分析的任务。此外，在考虑通用系统的性能时，计算变得更加复杂，该系统的故障事件被表示为切割集的链接集。这是因为即使组件事件具有光滑且凸极态函数，系统极限状态函数既没有属性，否则在琐碎的情况下。为了应对挑战，本研究开发了一种有效的算法来解决一般系统事件的RBO问题。我们采用缓冲的优化和可靠性方法（BORM），该方法利用了常规的故障概率定义，而不是缓冲失败的概率。所提出的算法通过采用近端捆绑方法迭代地迭代解决了一系列差异RBO模型。为了进行演示，我们设计了三个具有越来越复杂的数值示例，其中包括多达108个切割组，这些数字示例在一分钟内通过提出的算法以高精度来解决。我们还通过进行广泛的参数研究来证明其鲁棒性。
Reliability-based optimization (RBO) is crucial for identifying optimal risk-informed decisions for designing and operating engineering systems. However, its computation remains challenging as it requires a concurrent task of optimization and reliability analysis. Moreover, computation becomes even more complicated when considering performance of a general system, whose failure event is represented as a link-set of cut-sets. This is because even when component events have smooth and convex limit-state functions, the system limit-state function has neither property, except in trivial cases. To address the challenge, this study develops an efficient algorithm to solve RBO problems of general system events. We employ the buffered optimization and reliability method (BORM), which utilizes, instead of the conventional failure probability definition, the buffered failure probability. The proposed algorithm solves a sequence of difference-of-convex RBO models iteratively by employing a proximal bundle method. For demonstration, we design three numerical examples with increasing complexity that includes up to 108 cut-sets, which are solved by the proposed algorithm within a minute with high accuracy. We also demonstrate its robustness by performing extensive parametric studies.
