As a result, the proposed method, which is robust to predicted quality and variation of responses, yields better results than traditional desirability function method. 因此，用該方法進(jìn)行優(yōu)化能得到比傳統滿(mǎn)意度函數法較好的結果，且對模型的預測能力和響應的波動(dòng)都具有穩健性。
This method uses the satisfactoriness function to establish objective programming that can determine the weight of multiple attributes. 該方法利用基于離差的滿(mǎn)意度函數，通過(guò)建立偏好度集結的目標規劃來(lái)確定層次分析法中的屬性權重。
