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Abstract
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.
Additional information
Notes on contributors
Young-Hyun Ko
Mr. Ko is a Ph. D. Candidate in the Division of Mechanical and Industrial Engineering. His email address is [email protected].
Kwang-Jae Kim
Dr. Kim is an Associate Professor in the Division of Mechanical and Industrial Engineering. He is a Member of ASQ. His email address is [email protected].
Chi-Hyuck Jun
Dr. Jun is a Professor in the Division of Mechanical and Industrial Engineering. He is a Member of ASQ. His email address is [email protected].
