A robust desirability function method for multi-response surface optimization considering model uncertainty |
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Authors: | Zhen He Peng-Fei Zhu Sung-Hyun Park |
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Institution: | 1. Department of Industrial Engineering, Tianjin University, Tianjin 300072, PR China;2. Department of Statistics, Seoul National University, Seoul 151-747, Republic of Korea |
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Abstract: | A robust desirability function approach to simultaneously optimizing multiple responses is proposed. The approach considers the uncertainty associated with the fitted response surface model. The uniqueness of the proposed method is that it takes account of all values in the confidence interval rather than a single predicted value for each response and then defines the robustness measure for the traditional desirability function using the worst case strategy. A hybrid genetic algorithm is developed to find the robust optima. The presented method is compared with its conventional counterpart through an illustrated example from the literature. |
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Keywords: | Quality management Robust optimization Multi-response surface optimization Desirability function Hybrid genetic algorithm |
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