Advanced Numerical Analysis


This course is the continuation of Numerical Analysis. The student will learn state-of-the-art algorithms for solving ordinary differential equations, nonlinear systems, and optimization problems. Moreover, the analysis of these algorithms and their efficient implementation will be discussed in some detail.


Prof. Dr. Daniel Kressner.


Michael Steinlechner.


Numerical Analysis, knowledge of MATLAB

Lecture Notes

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The complete lecture notes are now available as one single PDF (Version 22.5.2015)

Information on the exam

The exam takes place on

July, 3rd, 8:00-11:00, in room CM 1105 

Topics for the exam: examtopics.txt

Old exam from 2013 and corresponding solution

Your exam will be of similar style. Note that the course content has been slightly changed. Furthermore, the exam will not include Matlab, as this was already part of the graded exercise sheets.


Graded Exercises

Useful Material

  • Convex optimization I and II: Homepage of Stephen Boyd’s lecture at Stanford University. Links to lecture notes and video streams of all lectures.
  • GALAHAD: a library of Fortran 2003 packages for solving nonlinear optimization problems by Nick Gould, Dominique Orban, and Philippe Toint
  • CUTEst: a Constrained and Unconstrained Testing Environment (intergrated with GALAHAD) by Nick Gould, Dominique Orban, and Philippe Toint
  • KNITRO, L-BFGS, CG+ and others by the team of Jorge Nocedal