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Multiple Constrained Optimal Experimental Design

Authors
Myung-WookKahngYoungIlKim
Issue Date
Dec-2002
Publisher
한국통계학회
Keywords
Phi_AP; Phi_AP
Citation
Communications for Statistical Applications and Methods, v.9, no.3, pp.619 - 627
Journal Title
Communications for Statistical Applications and Methods
Volume
9
Number
3
Start Page
619
End Page
627
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/16449
ISSN
2287-7843
Abstract
It is unpractical for the optimal design theory based on the given model and assumption to be applied to the real-world experimentation. Particularly, when the experimenter feels it necessary to consider multiple objectives in experimentation, its modified version of optimality criteria is indeed desired. The constrained optimal design is one of many methods developed in this context. But when the number of constraints exceeds two, there always exists a problem in specifying the lower limit for the efficiencies of the constraints because the "infeasible solution" issue arises very quickly. In this paper, we developed a sequential approach to tackle this problem assuming that all the constraints can be ranked in terms of importance. This approach has been applied to the polynomial regression model.
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