Design of Experiments: An Overview
AbstractDesign Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis including factor screening and optimization. This contribution starts with classic DOE including 2k-p and Central Composite designs. Next, it discusses factor screening through Sequential Bifurcation. Then it discusses Kriging including Latin Hyper cube Sampling and sequential designs. It ends with optimization through Generalized Response Surface Methodology and Kriging combined with Mathematical Programming, including Taguchian robust optimization.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2008-70.
Date of creation: 2008
Date of revision:
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Web page: http://center.uvt.nl
simulation; sensitivity analysis; optimization; factor screening; Kriging; RSM; Taguchi;
Find related papers by JEL classification:
- C0 - Mathematical and Quantitative Methods - - General
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-01-31 (All new papers)
- NEP-CBA-2009-01-31 (Central Banking)
- NEP-CMP-2009-01-31 (Computational Economics)
- NEP-EXP-2009-01-31 (Experimental Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Dellino, G. & Kleijnen, J.P.C. & Meloni, C., 2008.
"Robust Optimization in Simulation: Taguchi and Response Surface Methodology,"
2008-69, Tilburg University, Center for Economic Research.
- Dellino, Gabriella & Kleijnen, Jack P.C. & Meloni, Carlo, 2010. "Robust optimization in simulation: Taguchi and Response Surface Methodology," International Journal of Production Economics, Elsevier, vol. 125(1), pages 52-59, May.
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