Mathematical Algorithmic Optimization - Otto-von-Guericke-University Magdeburg


Compact Course: Optimization with Differential Equations

The compact course Optimization with Differential Equations will be held within SS 2012 for master-, diploma, and PhD-students at the Otto-von-Guericke-Universität Magdeburg / Max-Planck Institute Magdeburg.

The main goal of this compact course is to provide insight into the state of the art of the research area Optimization of Dynamic Processes. To this end, the foundations will be taught in a tutorial part with hands-on practical exercises. In a second part, current research projects will be presented by people working in the field.

The block course will build on a compact overview of deterministic optimization algorithms, derivative generation, and extensions towards optimal control. The theoretic overview will be complemented by practical hands-on exercises in the computer pool.

The three to four day introduction will be followed by one or two days with PhD students and invited external researchers reporting on state of the art projects in the field of optimization with differential equations.


The course is organized and taught by Sebastian Sager with support by Holger Diedam and Kathrin Hatz.

Preliminary program

The preliminary program reads as follows. The first three days comprise lectures and hands-on exercises:

Time Monday Tuesday Wednesday
09h00-10h00 Dynamic Process Models Optimal control: An Overview Mixed-Integer Optimal Control
10h00-10h15 Break
10h15-11h15 Nonlinear Programming Direct Multiple Shooting Parameter Estimation
11h15-11h30 Break
11h30-12h30 Numerical solution of ODEs Robust control, NMPC Optimum Experimental Design
12h30-14h00 Lunch
14h-18h00 Practical exercises:
AMPL + optimization
Practical exercises:
AMPL + optimal control
Practical exercises:
AMPL + dynamic optimization

Thursday and Friday comprise hands-on exercises and selected talks that reflect state-of-the art research in the field of Optimization with Differential Equations. The talks are scheduled for no more than 30 minutes and shall be complemented by at least 15 minutes of discussion.

Time Thursday Friday
09h00-9h45 Exam Christian Kirches: A real-time iteration scheme for mixed-integer nonlinear model predictive control
09h45-10h30 Feedback and open discussion Holger Diedam: Global optimal control using direct multiple shooting
10h30-11h00 Break
11h00-11h45 Martin Stoll: An introduction to iterative solvers for KKT systems Kathrin Hatz: Hierarchical Dynamic Optimization - Numerical Methods and Computational Results for Estimating Parameters in Optimal Control Problems
11h45-12h30 Matthias Voigt: H-infinity-Norm Computation for Large-Scale Descriptor Systems via Optimization over Structured Pseudospectra Janick Frasch: Multi- and Mixed-Level Iteration Schemes for Fast Nonlinear Model Predictive Control
12h30-14h00 Lunch
14h00-14h45 Philipp Rumschinski: Set-based estimation of nonlinear systems via semidefinite and linear relaxations Tony Huschto: Solving Stochastic Optimal Control Problems by a Polynomial Chaos Approach
14h45-15h30 Anton Savchenko: Fault diagnosis for hybrid and quantized systems Michael Jung: Minimization of Sewage Network Overflow
15h30-18h00 Practical exercises End of course

Slides will be distributed for all lectures.


Please send an email to if you want to participate and have not given your data at the Vorbesprechung.

Last Modification: 2016-05-12 - Contact Person: Sebastian Sager - Impressum