Abstract
Many engineering applications require to optimize the system performance
subject to reliability constraints, which are are commonly referred to as the
reliability based optimization (RBO) problems. In this work we propose a
derivative-free trust-region(DF-TR) based algorithm to solve the RBO problems.
In particular, we are focused on the type of RBO problems where the objective
function is deterministic and easy to evaluate, whereas the main challenge
arises from the reliability constraints. The proposed algorithm consists of
solving a set of subproblems, in which simple surrogate models of the
reliability constraints are constructed and used in solving the subproblems.
Taking advantage of the special structure of the RBO problems, we employ a
sample reweighting method to evaluate the failure probabilities, which
constructs the surrogate for the reliability constraints by performing only a
single full reliability evaluation in each iteration. Finally we demonstrate
the performance of the proposed method with both academic and practical
examples.
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