A Continuation Method for the Efficient Solution of Parametric Optimization Problems in Kinetic Model Reduction
Model reduction methods often aim at an identification of slow invariant manifolds in the state space of dynamical systems modeled by ordinary differential equations. We present a predictor corrector method for a fast solution of an optimization problem the solution of which is supposed to approxima...
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Veröffentlicht in: | SIAM journal on scientific computing 2013-01, Vol.35 (3), p.A1584-A1603 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Model reduction methods often aim at an identification of slow invariant manifolds in the state space of dynamical systems modeled by ordinary differential equations. We present a predictor corrector method for a fast solution of an optimization problem the solution of which is supposed to approximate points on slow invariant manifolds. The corrector method is either an interior point method or a generalized Gauss--Newton method. The predictor is an Euler prediction based on the parameter sensitivities of the optimization problem. The benefit of a step size strategy in the predictor corrector scheme is shown by means of an example. [PUBLICATION ABSTRACT] |
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ISSN: | 1064-8275 1095-7197 |
DOI: | 10.1137/120900344 |