A single-loop shifting vector method with conjugate gradient search for reliability-based design optimization. Issue 6 (3rd June 2021) - Biswas, Raktim; Sharma, Deepak
Abstract : Single-loop methods for reliability-based design optimization are characterized by high computational efficiency. However, the accuracy of these methods may be low for highly nonlinear probabilistic constraints. A new hybrid method called 'SLShV-CG' is proposed for improving accuracy in which the single-loop method is coupled with the shifting vector approach of the sequential optimization and reliability assessment method. This shifting vector approach is incorporated with the probabilistic constraints without approximating them for reliability analysis. The most probable points for the probabilistic constraints are found using the Karush–Kuhn–Tucker conditions and the conjugate gradient search direction is used for determining the approximate most probable point in every iteration. The proposed method is tested on four mathematical and four engineering reliability-based design optimization problems, and the accuracy of the solutions is verified using Monte Carlo simulations. The results demonstrate the better accuracy and computational efficiency of the proposed method over six reliability-based design optimization methods from the literature.