PDE constrained optimization

Monday, March 14, 2016 - 3:00pm - 4:00pm
Matthias Heinkenschloss (Rice University)
Many science and engineering problems lead to optimization problems governed by partial differential equations (PDEs), and in many of these problems some of the problem data are not known exactly. I focus on a class of such optimization problems where the uncertain data are modeled by random variables or random fields, and where decision variables (controls/designs) are deterministic and have to be computed before the uncertainty is observed. It is important that the uncertainty in problem data is adequately incorporated into the formulation of the optimization problem.
Friday, March 18, 2016 - 11:30am - 12:00pm
Michael Hinze (Universität Hamburg)
We consider optimal control of surface PDEs with special emphasis on tailored discretization of the underlying optimal control problem. We numerically analyze the errors stemming from the discretization of the surface and of the finite element discretization of the surface PDE. We present numerical examples which support our numerical findings.
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