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Direct Optimization: Problem discretization

  • Andreas Potschka
Chapter
Part of the Advances in Numerical Mathematics book series (ANUM)

Abstract

The goal of this chapter is to obtain a discretized version of OCP (2.6). We discuss a so-called direct approach and summarize its main advantages and disadvantages in Section 3.1 in comparison with alternative approaches. In Sections 3.2 and 3.3 we discretize OCP (2.6) in two steps. First we discretize in space and obtain a large-scale ODE constrained OCP which we then discretize in time to obtain a large-scale Nonlinear Programming Problem (NLP) presented in Section 3.5. The numerical solution of this NLP is the subject of Part II in this thesis.

Keywords

Direct Optimization Sequential Quadratic Programming Method Dimensional Optimization Problem Dimensional Space Versus Fast Local Convergence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Fachmedien Wiesbaden 2014

Authors and Affiliations

  1. 1.HeidelbergGermany

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