4:30 PM-6:30 PM
Optimal control problems typically evolve from simulation tasks defining some output states to be changed by some input controls. Despite the resulting large number of variables, methods treating the states and the controls together as unknowns of a discretized finite dimensional constrained optimization problem and applying SQP type algorithms have proven to be very efficient. The aim of this minisymposium is to highlight certain aspects of this approach in the context of ordinary as well as of partial differential equations. The minisymposium should be profitable for researchers interested in state-of-the-art solvers for discretized optimal control problems.
For Part II, see MS21a.
Organizers: Volker H. Schulz
University of Stuttgart, Germany
Hans Georg Bock
University of Heidelberg, Germany
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