Adaptive importance sampling for optimization under uncertainty problems

DOI10.1016/j.cma.2014.06.025zbMath1423.74733OpenAlexW1967593009MaRDI QIDQ1668392

Juan Camilo Medina, Alexandros A. Taflanidis

Publication date: 28 August 2018

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2014.06.025

zbMATH Keywords

stochastic optimizationimportance samplingrobust optimizationoptimization under uncertaintysimultaneous perturbation stochastic approximationkernel density approximation

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59) Optimization of other properties in solid mechanics (74P10)

Related Items (2)

A Bayesian approach for quantile optimization problems with high-dimensional uncertainty sources ⋮ Sequential approximate optimization for design under uncertainty problems utilizing Kriging metamodeling in augmented input space

Uses Software

• TOMLAB

Cites Work

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