A derivative-free trust-region algorithm for reliability-based optimization

Tian Gao, Jinglai Li

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)1535–1539
JournalStructural and Multidisciplinary Optimization
Volume55
Issue number4
Early online date24 Sep 2016
DOIs
Publication statusPublished - 24 Apr 2017

Keywords

  • derivative free
  • trust region
  • Monte Carlo
  • reliability based optimization

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