Abstract
A multiobjective optimization method considering uncertainty such as a reliability-based multiobjective design(RBMO) is useful for huge or complicated design problem considering uncertainty such as aerospace structures. In RBMO, the reliability constraint is evaluated through the reliability analysis such as the first order reliability method (FORM). The reliability analysis generally requires the probabilistic distribution parameters of random values such as material properties or applied loads. For example, the FORM converts the probabilistic distribution into the standardized normal distribution. However, under the actual design conditions, it is sometimes difficult to estimate the probabilistic parameters with high accuracy because of lack of information such as the limited number of experiments. In that case, the distribution parameters also have considered as uncertainties that can be evaluated through the confidence level. Then, this study proposes the distribution parameter estimation method considering uncertainties. This study addresses to investigate the effect of the parameter uncertainties on the RBMO using the confidence interval of Pareto solutions.
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