Robust optimization of multistage process: response surface and multi-response optimization approaches

被引:4
|
作者
Moslemi, Amir [1 ]
Seyyed-Esfahani, Mirmehdi [2 ]
机构
[1] Islamic Azad Univ, Fac Engn, Dept Ind Engn, West Tehran Branch, Tehran, Iran
[2] Amirkabir Univ Technol, Dept Ind Engn & Management Syst, Tehran, Iran
关键词
epsilon-constraints; global criterion (GC) method; multi-response optimization; multi-response surface; multistage process; multivariate robust regression; REGRESSION; MULTICOLLINEARITY; IMPROVEMENT; ESTIMATOR; SYSTEMS; SQUARES;
D O I
10.1515/ijnsns-2017-0003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A multistage system refers to a system contains multiple components or stages which are necessary to finish the final product or service. To analyze these problems, the first step is model building and the other is optimization. Response surfaces are used to model multistage problem as an efficient procedure. One regular approach to estimate a response surface using experimental results is the ordinary least squares (OLS) method. OLS method is very sensitive to outliers, so some multivariate robust estimation methods have been discussed in the literature in order to estimate the response surfaces accurately such as multivariate M-estimators. In optimization phase, multi-response optimization methods such as global criterion (GC) method and E-constraints approaches are different methods to optimize the multi-objective-multistage problems. An example of the multistage problem had been estimated considering multivariate robust approaches, besides applying multi-response optimization approaches. The results show the efficiency of the proposed approaches.
引用
收藏
页码:163 / 175
页数:13
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