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Design of Experiments. Design of Experiments (DOE) is a study of the factors that the team has determined are the key process input variables (KPIV's) that are the source of the variation or have an influence on the mean of the output. A DOE (or set of DOE's) will help develop a prediction equation for the process in terms of Y = f(X1,X2,X3,X4,....Xn).
Suppose you wish to solve the product-mix problem. Launch the LINDO package. We will use XR and XE to denote the decision variables. In the current window, enter: Note that. 1  In LINDO, the minute you use a variable in your model, it exists. 2  You don't have to do anything other than enter it in a formula.ote that. 1  In LINDO, the minute you use a variable in your model, it exists. 2  LINDO interprets the 3  . The objective function should not contain any constant. 4  All variables must appear on the left-hand side of the constraints, while numerical values must appear on the right-hand side of the constraints. 5  All variables are assumed to be nonnegative.