Computational Results in Selecting Multi-Factor Experimental Arrangements
John B. Neuhardt, Hugh E. Bradley, Richard W. Henning · Journal of the American Statistical Association · 1973
This article investigates some theoretical and computational properties dealing with the selection of an “optimum” experiment in a constrained environment. The squared Euclidean norm of the information matrix is developed as a measure of optimality for any experimental factorial arrangement. The problem of experimental layout is structured as a mathematical optimization which can be transformed into a quadratic integer program. Computational results are given.