  We present a novel approach, referred to as the 'threshold shift method'
(TSM), for reliability based design optimization (RBDO). The proposed approach
is similar in spirit with the sequential optimization and reliability analysis
(SORA) method where the RBDO problem is decoupled into an optimization and a
reliability analysis problem. However, unlike SORA that utilizes shift-vector
to shift the design variables within a constraint (independently), in TSM we
propose to shift the threshold of the constraints. We argue that modifying a
constraint, either by shifting the design variables (SORA) or by shifting the
threshold of the constraints (TSM), influences the other constraints of the
system. Therefore, we propose to determine the thresholds for all the
constraints by solving a single optimization problem. Additionally, the
proposed TSM is equipped with an active-constraint determination scheme. To
make the method scalable, a practical algorithm for TSM that utilizes two
surrogate models is proposed. Unlike the conventional RBDO methods, the
proposed approach has the ability to handle highly non-linear probabilistic
constraints. The performance of the proposed approach is examined on six
benchmark problems selected from the literature. The proposed approach yields
excellent results outperforming other popular methods in literature. As for the
computational efficiency, the proposed approach is found to be highly
efficient, indicating it's future application to other real-life problems.

Numerical Analysis