Abstract
The Single Loop Single Vector (SLSV) approach for reliability-based design optimization (RBDO) is integrated with Augmented Lagrangian (AL) formulation of analytical target cascading for solution of hierarchical multilevel optimization problems under uncertainty. In the proposed SLSV+AL approach, the uncertainties are propagated by matching the required moments of connecting responses/targets and linking variables present in the decomposed system. The accuracy and computational efficiency of SLSV+AL are demonstrated through the solution of three benchmark problems and comparison of results with those from other optimization methods reported in the literature. The results are presented and discussed.
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