The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 19, 2009
Filed:
Apr. 28, 2005
Rajesh V. Subbu, Clifton Park, NY (US);
Piero P. Bonissone, Schenectady, NY (US);
Neil H. Eklund, Schenectady, NY (US);
Naresh S. Iyer, Clifton Park, NY (US);
Rasiklal P. Shah, Latham, NY (US);
Weizhong Yan, Clifton Park, NY (US);
Chad E. Knodle, Dayton, NV (US);
James J. Schmid, Kirkland, WA (US);
Rajesh V. Subbu, Clifton Park, NY (US);
Piero P. Bonissone, Schenectady, NY (US);
Neil H. Eklund, Schenectady, NY (US);
Naresh S. Iyer, Clifton Park, NY (US);
Rasiklal P. Shah, Latham, NY (US);
Weizhong Yan, Clifton Park, NY (US);
Chad E. Knodle, Dayton, NV (US);
James J. Schmid, Kirkland, WA (US);
General Electric Company, Schenectady, NY (US);
Abstract
A method and system for performing model-based multi-objective asset optimization and decision-making is provided. The method includes building at least two predictive models for an asset. The building includes categorizing operational historical data via at least one of: controllable variables, uncontrollable variables, output objectives, and constraints. The building also includes selecting at least two output objectives or constraints, and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints. The method also includes validating each predictive model and performing multi-objective optimization using the predictive models. The multi-objective optimization includes specifying search constraints and applying a multi-objective optimization algorithm. The method further includes generating a Pareto Frontier, and selecting a Pareto optimal input-output vector.