A generalized “max-min” sample for surrogate update

A generalized “max-min” sample for surrogate update

This brief note describes the generalization of the “max-min” sample that was originally used in the update of approximated feasible or failure domains. The generalization stems from the use of the random variables joint distribution in the sampling scheme. In addition, this note proposes a numerica...

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Veröffentlicht in:Structural and multidisciplinary optimization 2014-04, Vol.49 (4), p.683-687
Hauptverfasser: Lacaze, Sylvain, Missoum, Samy
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container_title Structural and multidisciplinary optimization
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creator Lacaze, Sylvain
Missoum, Samy
description This brief note describes the generalization of the “max-min” sample that was originally used in the update of approximated feasible or failure domains. The generalization stems from the use of the random variables joint distribution in the sampling scheme. In addition, this note proposes a numerical improvement of the max-min optimization problem through the use of the Chebychev norm.
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Computational Mathematics and Numerical Analysis
Domains
Engineering
Engineering Design
Optimization
Random variables
Theoretical and Applied Mechanics
title A generalized “max-min” sample for surrogate update
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