Abstract
During metamodel-based optimization three types of implicit errors are typically made.The first error is the simulation-model error, which is defined by the difference between reality and the computer model.The second error is the metamodel error, which is defined by the difference between the computer model and the metamodel.The third is the implementation error.This paper presents new ideas on how to cope with these errors during optimization, in such a way that the final solution is robust with respect to these errors.We apply the robust counterpart theory of Ben-Tal and Nemirovsky to the most frequently used metamodels: linear regression and Kriging models.The methods proposed are applied to the design of two parts of the TV tube.The simulationmodel errors receive little attention in the literature, while in practice these errors may have a significant impact due to propagation of such errors.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
