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Design of Experiments (DOE) is a methodology that defines an optimal set of experiments in the design space, in order to obtain the most relevant information possible with the highest accuracy at the least cost.
OPTIMUS counts two families of DOE methods. The traditional DOE methods are based on statistical criteria and include among others Full and Factorial Designs, Central Composite Designs, Random and Latin Hypercube Designs, Placket-Burman, Box-Behnken and Taguchi Designs. The second group consists of Optimal DOE methods, which are based on mathematical optimality criteria. These DOE methods include I-Optimal, D-Optimal and A-Optimal Designs.
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