An incremental shifting vector approach for reliability-based design optimization

Abstract

This paper proposes a decoupling algorithm for reliability-based design optimization (RBDO) with high performance in terms of efficiency and convergence, which provides an effective tool for reliability design of many complex structures. The algorithm proceeds by performing a shifting vector calculation and then solving a deterministic design optimization in each step, and eventually converges to the optimal solution. An incremental shifting strategy is proposed to ensure stable convergence in the iteration process. In each step, the shifting vector preserves the information from the previous step, and only an adjustment is made for it through a shifting vector increment. A computation method is given for the shifting vector increment, avoiding solving an optimization problem during the reliability analysis and thus greatly reducing the computational cost of the iteration process. Six numerical examples and two engineering applications are presented to validate the effectiveness of the method proposed in this paper.

An Efficient Quantile-Based Adaptive Sampling RBDO with Shifting Constraint Strategy

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An uncertainty propagation analysis method considering multimodal random distribution

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A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

“…For some complex cases, such as the constraint with multiple MLPs, the differences between the shifting vectors of adjacent iteration steps can be large, which may lead to numerical oscillations and whereby impact the convergence of the iteration process. 30 To improve convergence, the concept of increment 40 recently proposed by the authors is introduced, which is calculated in the kth iteration step for fine-tuning the shifting vector in the (k-1)th iteration step. This fine-tuning process can be expressed as S (k) = S (kÀ1) + DS (k) .…”