Multiresponse optimization with consideration of probabilistic covariates
Article first published online: 25 AUG 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 27, Issue 4, pages 437–449, June 2011
How to Cite
Hejazi, T. H., Bashiri, M., Noghondarian, K. and Atkinson, A. C. (2011), Multiresponse optimization with consideration of probabilistic covariates. Qual. Reliab. Engng. Int., 27: 437–449. doi: 10.1002/qre.1133
- Issue published online: 23 MAY 2011
- Article first published online: 25 AUG 2010
- multiple response optimization;
- dual response surfaces (DRS);
- covariate effect;
- goal programming (GP);
- stochastic modeling
In many complex experiments, nuisance factor may have large effects that must be accounted for. Covariates are one of the most important kinds of nuisance factors that can be measured but cannot be controlled within the experimental runs. In this paper a novel approach is proposed, based on goal programming, to find the best combination of factors so as to optimize multiresponse-multicovariate surfaces with consideration of location and dispersion effects. Furthermore, it is supposed that several covariates considered in the experiment have probability distributions of known form. One objective is to find the most probable values of each covariate. For this purpose, a multiobjective mathematical optimization model is proposed and its efficacy is demonstrated by two numerical examples. Copyright © 2010 John Wiley & Sons, Ltd.