Mathematics > Optimization and Control
[Submitted on 24 Sep 2014 (v1), last revised 6 Aug 2015 (this version, v2)]
Title:A density-matching approach for optimization under uncertainty
View PDFAbstract:Modern computers enable methods for design optimization that account for uncertainty in the system---so-called optimization under uncertainty. We propose a metric for OUU that measures the distance between a designer-specified probability density function of the system response the target and system response's density function at a given design. We study an OUU formulation that minimizes this distance metric over all designs. We discretize the objective function with numerical quadrature and approximate the response density function with a Gaussian kernel density estimate. We offer heuristics for addressing issues that arise in this formulation, and we apply the approach to a CFD-based airfoil shape optimization problem. We qualitatively compare the density-matching approach to a multi-objective robust design optimization to gain insight into the method.
Submission history
From: Pranay Seshadri [view email][v1] Wed, 24 Sep 2014 20:35:16 UTC (2,389 KB)
[v2] Thu, 6 Aug 2015 20:47:37 UTC (2,181 KB)
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