A new loss function-based method for multiresponse optimization is presented. The proposed method introduces predicted future responses in a loss function, which accommodates robustness and quality of predictions as well as bias in a single framework. Properties of the proposed method are illustrated with two examples. We show that the proposed method gives more reasonable results than the existing methods when both robustness and quality of predictions are important issues.
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