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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization
verfasst von : Derya B. Özyurt, Paul I. Barton
Erschienen in: Automatic Differentiation: Applications, Theory, and Implementations
Verlag: Springer Berlin Heidelberg
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A targeted AD approach is presented to calculate directional second order derivatives of ODE/DAE embedded functionals accurately and eficiently. This advance enables us to tackle the solution of large scale dynamic optimization problems using a truncated-Newton method where the Newton equation is solved approximately to update the direction for the next optimization step. The proposed directional second order adjoint method (dSOA) provides accurate Hessian-vector products for this algorithm. The implementation of the “dSOA powered” truncated- Newton method for the solution of large scale dynamic optimization problems is showcased with an example.