An Integrative Loss Function Approach to Multi‐Response Optimization
An Integrative Loss Function Approach to Multi‐Response Optimization
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DOI：
10.1002/qre.1571
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发表时间：
2015-03
影响因子：
2.3
通讯作者：
Linhan Ouyang;Yizhong Ma;J. Byun
中科院分区：
文献类型：
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作者：
Linhan Ouyang;Yizhong Ma;J. Byun
损失函数法是一种有效的多响应优化方法。然而，以往的损失函数方法忽略了误差平方损失和模型不确定性的色散性能。本文提出了一种加权损失函数，同时考虑误差平方损失的位置和色散特性，以优化具有模型不确定性的相关多重响应。在多个响应的未来预测的置信区间应包含在响应的规范极限的约束下，我们提出了一种最小化加权损失函数的方法。算例验证了该方法的有效性。结果表明，在模型不确定的情况下，该方法能获得可靠的最优运行状态。版权所有©2013 John Wiley & Sons， Ltd
Loss function approach is effective for multi‐response optimization. However, previous loss function approaches ignore the dispersion performance of squared error loss and model uncertainty. In this paper, a weighted loss function is proposed to simultaneously consider the location and dispersion performances of squared error loss to optimize correlated multiple responses with model uncertainty. We propose an approach to minimize the weighted loss function under the constraint that the confidence intervals of future predictions for the multiple responses should be contained in specification limits of the responses. An example is illustrated to verify the effectiveness of the proposed method. The results show that the proposed method can achieve reliable optimal operating condition under model uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.