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• W2158196689 abstract "Design 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 and optimization. This contribution starts with classic DOE including 2k--p and Central Composite Designs (CCDs). Next, it discusses factor screening through Sequential Bifurcation. Then it discusses Kriging including Latin Hypercube Sampling and sequential designs. It ends with optimization through Generalized Response Surface Methodology and Kriging combined with Mathematical Programming, including Taguchian robust optimization." @default.
• W2158196689 created "2016-06-24" @default.
• W2158196689 creator A5087315126 @default.
• W2158196689 date "2008-12-07" @default.
• W2158196689 modified "2023-09-25" @default.
• W2158196689 title "Design of experiments: overview" @default.
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• W2158196689 doi "https://doi.org/10.5555/1516744.1516836" @default.
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