An Adjustment Algorithm for the Construction of ExactD-Optimum Experimental Designs

Abstract
Existing algorithms for the construction of exact D-optimum designs customarily search a list of candidate points. This article describes a computationally simple method of improving such designs. Tables are given of designs for second-order models with as many as five factors found by search over candidate points. These are compared with designs already in the literature and used as the starting point for the adjustment algorithm.