Many problems in science and engineering are formulated as optimization problems governed by partial differential equations. Mathematical and computational techniques in this field have enabled the solution of complex problems ranging from image processing to fluid flow. However, in most applications the model parameters such as diffusivity in the heat equation or certain reaction rates in reaction-diffusion equations are not known exactly and are therefore modelled as uncertain parameters. This poses a significant challenge since besides having to represent the spatial and temporal components the random variables inherent in the system have to be accounted for. We want to illustrate the latest developments in enabling and understanding PDE-constrained optimization problems under uncertainty with contributions including topics such as the numerical solution of high-dimensional systems or robust optimization methods.
Organizers: Martin Stoll (Magdeburg)
- Stefan Ulbrich (TU Darmstadt): "tba"
- Christian Kirches (TU Braunschweig): "tba"
- Claudia Schillings (University of Mannheim): "tba"
- Peter Benner (MPI Magdeburg): "tba"