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Enhanced Sequential Optimization and Reliability Assessment method for probabilistic optimization with varying design variance

机译：改进的序贯优化和可靠性评估方法，用于变化设计方差的概率优化

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摘要

The Sequential Optimization and Reliability Assessment (SORA) method is a single-loop method containing a serial of cycles of decoupled deterministic optimization and reliability assessment for improving the efficiency of probabilistic optimization. However, the original SORA method as well as some other existing single-loop methods do not take into account the effect of varying design variance (changing variance) in design problems. In this paper, to enhance the SORA method, three formulations are proposed in order to improve the efficiency for solving problems with changing variance. These formulations are categorized by the different strategies of Inverse Most Probable Point (IMPP) approximation. Mathematical examples and a speed reducer design problem are utilized to test and compare the effectiveness of the proposed formulations. The insight gained from our study on the applicability of different approaches can be extended and utilized in other probabilistic optimization strategies that require IMPP estimations.
机译：顺序优化和可靠性评估（SORA）方法是一种单环方法，包含一系列解耦的确定性优化和可靠性评估循环，以提高概率优化的效率。但是，原始的SORA方法以及其他一些现有的单循环方法未考虑设计问题中变化的设计方差（变化的方差）的影响。为了改进SORA方法，本文提出了三种公式，以提高解决方差变化问题的效率。这些公式按最可能逆点（IMPP）近似的不同策略进行分类。通过数学示例和减速器设计问题来测试和比较所提出配方的有效性。从我们对不同方法的适用性的研究中获得的见识可以扩展并用于需要IMPP估计的其他概率优化策略中。

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