Compact Course Optimization

The compact course Mathematical Complexity Reduction: Optimization (LSF) will be held within SS 2017 for PhD students of the Research Training Group. Interested master and PhD students, e.g., from the Faculty of Mathematics or the IMPRS, may also participate if places are available (Wahlfach).

The main goal of this compact course is to provide insight into the state of the art of the research area Optimization. To this end, the foundations will be taught in a tutorial part with hands-on practical exercises. In addition, a more detailed exposition of complexity reduction aspects will be given.

The block course will build on a compact overview of deterministic optimization algorithms for Linear Optimization, Nonlinear Optimization, Polynomial Optimization, Mixed-integer Nonlinear Optimization, and Dynamic Optimization. The focus of the complexity reduction part will be on approximation hierarchies and their relation to Positivstellensätze, and lifting, such as the Lifted Newton method.

The theoretic overview will be complemented by practical hands-on exercises on participants' notebooks. Please bring your notebook, ideally with Matlab or Octave already installed. Using AMPL or CasADi is optional. You can download slides, exercise sheets, AMPL executables and more from this password protected page.

  • Date: June 26-July 7, 9h15-13h30, including breaks
  • Duration: Equivalent to 4SWS.
  • Place: G03-019 (ground floor corner between building G02 and G03)
  • The course will be taught in English

The course is organized and taught by Gennadiy Averkov and Sebastian Sager.

Preliminary program

The preliminary program reads as follows.

First part, lectures given by Sebastian Sager.

In addition, there will be a talk within the MALOC lecture series on Tuesday, 17h00, in the Lukasklause, which is part of the compact course. Claudia Schillings is talking about Uncertainty quantification in inverse problems.

Second part, lectures given by Gennadiy Averkov.

Time Mon, July 3 Tue, July 4 Wed, July 5 Thu, July 6 Fri, July 7
8:00-9:30 Introduction Real Algebra Stellensätze Conic Optimization Interior-point methods for semidefinite optimization
10:00-11:30 Real algebra Stellensätze Conic optimization Semidefinite optimization Software session (Baron, Sedumi etc.)
12:30-13:30 Real algebra Exercises Exercises Exercises Software session

Please send an email to if you want to participate.

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