System and method for optimization process repeatability in...

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Reexamination Certificate

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Reexamination Certificate

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08036921

ABSTRACT:
A method (and system) of providing optimization repeatability in an on-demand computing environment removes variability in an optimization model instance and can be exemplarily implemented in a service architecture. The method and system receives a plurality of physical data instances, which are different representations of the same logical data model, and transforms the plurality of physical data instances into a normalized physical data instance, which can be combined with an optimization model to form a unique optimization model instance, thereby providing repeatability in solving optimization problems.

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François M. Hemez1 and Scott W. Doeblin, “Model Validation and Uncertainty Quantification” A Special Session of the SD-2000 (Structural Dynamics 2000) Forum, Proceedings of IMAC-XIX, the 19th International Modal Analysis Conference. Feb. 5-8, 2001, Kissimmee, Florida.
François M. Hemez and Scott W. Doeblin, “Model Validation and Uncertainty Quantification” A Special Session of the SD-2000 (Structural Dynamics 2000) Forum, Proceedings of IMAC-XIX, the 19th International Modal Analysis Conference. Feb. 5-8, 2001, Kissimmee, Florida.
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