Title
Balancing the Subjective and Objective Weights for Correlated Multiresponse Optimization.
Abstract
Desirability function approach is very popular for multiresponse optimization problems. However, the approach ignores the correlations among multiple responses and does not consider how to reasonably determine the relative weights of multiple responses. In this paper, an integrative desirability function approach is proposed to simultaneously consider the correlations among the responses and the weight determination method. For the proposed approach, the root mean square error performance is regarded as a new response, and then the seemingly unrelated regression estimation is utilized to fit the models. Through balancing the subjective and objective information, the proposed approach can be used to make more reasonable decisions for correlated multiresponse optimization. Two examples are employed to validate the effectiveness of the proposed approach. Copyright (c) 2015 John Wiley & Sons, Ltd.
Year
DOI
Venue
2016
10.1002/qre.1794
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Keywords
Field
DocType
desirability function approach,multiresponse optimization,correlation,subjective and objective weights,root mean square error
Econometrics,Mathematical optimization,Mean squared error,Correlation,Seemingly unrelated regressions,Statistics,Optimization problem,Mathematics,Desirability function
Journal
Volume
Issue
ISSN
32
3
0748-8017
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Liuyang Zhang100.34
Yizhong Ma2408.89
Linhan Ouyang381.24
Jian Liu400.68