Differential evolutionary algorithm in the construction process of optimal experimental designs

This article shows how a differential evolution algorithm can be used to find statistical designs under several optimality criteria as A, D, and T. The general algorithm of differential evolution is described and then applied on constructing optimal designs for several well-known models and compare them with those already available by other algorithms, in terms of relative efficiency. Moreover, the great effect of population size in the running of this algorithm establishes a precedent in the use of differential evolution algorithms over genetic algorithms.