An Integrative Loss Function Approach to Multi‐Response Optimization

Loss function approach is effective for multi-response optimization. However, previous loss function approaches ignore thedispersion performance of squared error loss and model uncertainty. In this paper, a weighted loss function is proposed tosimultaneously consider the location and dispersion performances of squared error loss to optimize correlated multipleresponseswith model uncertainty. We proposean approach tominimize the weighted loss function underthe constraint thatthe confidence intervals of future predictions for the multiple responses should be contained in specification limits of theresponses. An example is illustrated to verify the effectiveness of the proposed method. The results show that the proposedmethod can achieve reliable optimal operating condition under model uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.Keywords: loss function; model uncertainty; location and dispersion performances; confidence interval; specification limit

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