How does the MultiSimplex methods compare with ordinary statistical methods?
Ordinary statistical methods require the fulfillment of many assumptions about distribution, linearity, etc. The MultiSimplex methods are free from such assumptions and consequently easier to apply to most real world problems. Statistical design of experiments is a powerful methodology for gaining scientific insight, but to find optimum conditions it usually requires many more trials than the MultiSimplex methods. Multicriteria optimization objectives are also more difficult to apply.
