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We consider algorithmic approaches to the D-optimality problem for caseswhere the input design matrix is large and highly structured, in particularimplicitly specified as a full quadratic or linear response-surface model inseveral levels of several factors. Using row generation techniques ofmathematical optimization, in the context of discrete local-search andcontinuous relaxation aimed at branch-and-bound solution, we are able to designpractical algorithms.

Computing D-Optimal solutions for huge-scale linear and quadratic response-surface models