  For computing efficient approximate designs of multifactor experiments, we
propose a simple algorithm based on adaptive exploration of the grid of all
combinations of factor levels. We demonstrate that the algorithm significantly
outperforms several state-of-the-art competitors for problems with discrete,
continuous, as well as mixed factors. Importantly, we provide a free R code
that permits direct verification of the numerical results and allows the
researchers to easily compute optimal or nearly-optimal experimental designs
for their own statistical models.
