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A derivative-free trust-region algorithm for reliability-based optimization
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DOI：10.1007/s00158-016-1587-y.png)
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摘要
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In this note, we present a derivative-free trust-region (TR) algorithm for reliability based optimization (RBO) problems. 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. With numerical experiments, we illustrate that the proposed algorithm is competitive against existing methods.
Keyword:
Derivative free
Trust region
Monte Carlo
Reliability based optimization
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