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URN: urn:nbn:de:0030-drops-20009
URL: http://drops.dagstuhl.de/opus/volltexte/2009/2000/
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Poles, Silvia ; Lovison, Alberto

A Polynomial Chaos Approach to Robust Multiobjective Optimization

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Abstract

Robust design optimization is a modeling methodology, combined with a suite of computational tools, which is aimed to solve problems where some kind of uncertainty occurs in the data or in the model. This paper explores robust optimization complexity in the multiobjective case, describing a new approach by means of Polynomial Chaos expansions (PCE). The aim of this paper is to demonstrate that the use of PCE may help and speed up the optimization process if compared to standard approaches such as Monte Carlo and Latin Hypercube sampling.

BibTeX - Entry

@InProceedings{poles_et_al:DSP:2009:2000,
  author =	{Silvia Poles and Alberto Lovison},
  title =	{A Polynomial Chaos Approach to Robust Multiobjective Optimization},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  year =	{2009},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  number =	{09041},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2009/2000},
  annote =	{Keywords: Uncertainty Quantification, Multiobjective Robust Design, Monte Carlo, Latin Hypercube, Polynomial Chaos}
}

Keywords: Uncertainty Quantification, Multiobjective Robust Design, Monte Carlo, Latin Hypercube, Polynomial Chaos
Seminar: 09041 - Hybrid and Robust Approaches to Multiobjective Optimization
Issue Date: 2009
Date of publication: 11.05.2009


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