A Compromise Approach to Multiresponse Optimization

Practitioners often must choose optimum operating conditions for several responses simultaneously. Rarely is the resulting “optimum” truly optimal for all of the individual responses taken individually. Instead, the optimum represents some explicit compromise among the conflicting conditions. This paper proposes a mean squared error method which allows the practitioner to specify the directions of economic importance for the compromise optimum, while seriously considering the variance-covariance structure of the multiple responses. By looking at the mean square error, this approach seriously incorporates the variance-covariance structure of the multiple responses. An example illustrates the methodology.