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Reliability-based optimization algorithm using hybrid model with truncated probability and non-probability
Received date: 2016-03-11
Revised date: 2016-08-12
Online published: 2016-08-26
Supported by
National Natural Science Foundation of China (51305421); National Defence Technology Basis Research Project of China (JSZL2014130B005); Young Scholars Fund of Development Project of Science and Technology of Jilin Province (20140520137JH)
A new hybrid reliability model is presented for the case that truncated probabilistic variables and non-probabilistic variables exist simultaneously in engineering. Based on the new hybrid reliability model and reliability index assessment (RIA) method, a nested loop hybrid reliability-based optimization model is also presented. Modified ST-Powell optimization algorithm with better search strategy is used to search the optimal values of design variables in the out-loop. Modified limit step length iteration algorithm, which can ensure convergence, is used to solve the new hybrid reliability index in the inner-loop. Numerical examples show that the global optimization rate of the modified ST-Powell optimization algorithm with better search strategy can be promoted significantly, and the validity of hybrid reliability-based optimization model searched by the algorithm presented in this paper is proved. The algorithm can obtain the optimal values for hybrid reliability-based optimization model with high nonlinear limit state function. The algorithm presented in this paper has a good adaptability to hybrid reliability-based optimization problems of engineering structure.
ZHOU Ling , LI Yanhui . Reliability-based optimization algorithm using hybrid model with truncated probability and non-probability[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017 , 38(1) : 220216 -220216 . DOI: 10.7527/S1000-6893.2016.0233
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