Multiresponse optimisation of correlated responses: some analysis and results Online publication date: Mon, 14-Dec-2009
by Susanta Kumar Gauri, Surajit Pal
International Journal of Experimental Design and Process Optimisation (IJEDPO), Vol. 1, No. 2/3, 2009
Abstract: Although there are several methods to resolve multiresponse optimisation problems, only a few of them take care of the possible correlation among the responses. The relative performance of these methods is unknown and therefore, selection of the appropriate method becomes an important issue to the engineers. In this paper, the optimisation performance of three methods dealing with the multiple correlated responses, e.g., weighted principal component (WPC) method, principal component analysis (PCA)-based grey relational analysis (GRA) method and PCA-based technique for order preference by similarity to ideal solution (TOPSIS) method are compared. It is found that PCA-based GRA method result in the best optimisation when the correlations among the responses are quite weak. But the WPC and PCA-based TOPSIS methods result in equivalent and better optimisation when at least two responses are strongly correlated. However, WPC method is preferable because of its simpler computational procedure.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Experimental Design and Process Optimisation (IJEDPO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook