As will be shown the current use of Desirability Indices for optimisation purposes in experimental design gives biased results in general. Researchers were satisfied with approximative solutions as unbiased results would have required analytical expressions for the distributions of Desirability Indices. These expressions are unavailable. Today’s computing power allows to use Monte-Carlo estimators for estimating exact solutions instead of analytical solutions and therefore to improve the estimation process for Desirabilities.
MCO MCD MCDA Desirability Function Desirability Index numerical optimisation bias Monte-Carlo estimation computer intensive procedures