Multi-parametric Nonlinear Programming and the Evaluation of Implicit Optimization Model Adequacy
نویسندگان
چکیده
An algorithmic framework for numerically approximating multiparametric nonlinear programming (mp-NLP) solutions is given, along with a method that uses mp-NLP for evaluating the adequacy of the nominal model used in Implicit Optimization. The mp-NLP algorithm builds on numerical methods for single parameter nonlinear programming and for the approximation of implicit manifolds. An example problem is presented.
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