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. Todays 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
A desirability function approach has been widely used in multi-response optimization due to its simp...
AbstractThe computational cost of many computer codes is a burden that obliges users to use the same...
A review about the application of response surface methodology (RSM) when several responses have to ...
The basic ideas of Desirability functions and indices are introduced and compared to other methods o...
The basic ideas of Desirability functions and indices are introduced and compared to other methods o...
Desirability functions and desirability indices are powerful tools for multicriteria optimization un...
Pareto-Optimality and the Desirability Index are methods for multicriteria optimization in quality m...
Optimizing the quality of a product is widespread in the industry. Products have to be manufactured ...
Harrington’s desirability function approach is frequently used to overcome the problem of optimizati...
Optimizing the quality of a product is widespread in the industry. Products have to be manufactured ...
A shortfall of the Derringer and Suich (1980) desirability function is lack of inferential methods t...
Desirability functions (DFs) play an increasing role for solving the optimization of process or prod...
AbstractThe so-called a posteriori approach to optimization with multiple conflicting objective func...
The desirability index (DI) is a method for multi-criteria optimization accepted widely in industri...
Harrington’s desirability function approach is usually used to overcome the problem of optimization ...
A desirability function approach has been widely used in multi-response optimization due to its simp...
AbstractThe computational cost of many computer codes is a burden that obliges users to use the same...
A review about the application of response surface methodology (RSM) when several responses have to ...
The basic ideas of Desirability functions and indices are introduced and compared to other methods o...
The basic ideas of Desirability functions and indices are introduced and compared to other methods o...
Desirability functions and desirability indices are powerful tools for multicriteria optimization un...
Pareto-Optimality and the Desirability Index are methods for multicriteria optimization in quality m...
Optimizing the quality of a product is widespread in the industry. Products have to be manufactured ...
Harrington’s desirability function approach is frequently used to overcome the problem of optimizati...
Optimizing the quality of a product is widespread in the industry. Products have to be manufactured ...
A shortfall of the Derringer and Suich (1980) desirability function is lack of inferential methods t...
Desirability functions (DFs) play an increasing role for solving the optimization of process or prod...
AbstractThe so-called a posteriori approach to optimization with multiple conflicting objective func...
The desirability index (DI) is a method for multi-criteria optimization accepted widely in industri...
Harrington’s desirability function approach is usually used to overcome the problem of optimization ...
A desirability function approach has been widely used in multi-response optimization due to its simp...
AbstractThe computational cost of many computer codes is a burden that obliges users to use the same...
A review about the application of response surface methodology (RSM) when several responses have to ...