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Robust Design Optimization Approach by Combination of Sensitivity Analysis and Sigma Level Estimation

机译:灵敏度分析和Sigma水平估计相结合的鲁棒设计优化方法

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摘要

This paper proposes a novel robust optimization approach by combination of sensitivity analysis and sigma level estimation in multi-objective problems. In order to obtain robust Pareto-optima within acceptable computational costs, we actively reuse the already calculated data for the sensitivity analysis in multipoint search algorithm. The sigma level estimation is also utilized to select the significant solutions from a large number of Pareto-optima based on both the robustness and the performance. Some numerical results that verify the effectiveness of the proposed methods are presented.
机译:本文提出了一种灵敏度分析和西格玛水平估计相结合的多目标问题的鲁棒优化方法。为了在可接受的计算成本内获得鲁棒的帕累托最优,我们积极地将已经计算的数据重新用于多点搜索算法中的敏感性分析。 σ级别估计还基于健壮性和性能,从大量的帕累托最优中选择重要的解。提出了一些数值结果,验证了所提方法的有效性。

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