Multiresponse optimisation of correlated responses: some analysis and results

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.