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Multiple response surface optimization (MRSO) aims at finding a setting of input variables which simultaneously optimizes multiple responses. The minimization of mean squared error (MSE), which consists of the squared bias and variance terms, is an effective way to consider the location and dispersion effects of the responses in MRSO. This approach basically assumes that both the terms have an equal weight. However, they need to be weighted differently depending on a problem situation, for example, in case that they are not of the same importance. This paper proposes to use the weighted MSE (WMSE) criterion instead of the MSE criterion in MRSO to consider an unequal weight situation. Key Words : Multiple response surface optimization, Squared bias, Variance, Weighted mean squared error * Corresponding Author : In-Jun Jeong (Daegu University)Tel: +82-53-850-6275 email: ijjeong@daegu.ac.krReceived October 26, 2012 Revised January 2, 2013 Accepted February 6, 2013 1.

A Weighted Mean Squared Error Approach to Multiple Response Surface Optimization