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- W3142023185 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 2 <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>k-p</sup> 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.
- W3142023185 created "2021-04-13" @default.
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- W3142023185 date "2008-12-01" @default.
- W3142023185 modified "2023-09-25" @default.
- W3142023185 title "Design Of Experiments: Overview" @default.
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- W3142023185 doi "https://doi.org/10.1109/wsc.2008.4736103" @default.
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