Wednesday Night Workshop
PDE Constrained Optimization
Organized by: Eldad Haber

Optimal design, optimal control, and parameter estimation of
systems governed by partial differential equations give rise to a
class of problems known as PDE-constrained optimization. The size
and complexity of the discretized PDE constraints often pose
significant challenges for contemporary optimization methods.
Recent advances in algorithms, software, and high performance
computing systems have resulted in PDE simulations that can often
scale to millions of variables, thousands of processors, and
multiple physics interactions. As PDE solvers mature, there is
increasing interest in industry and the national labs in solving
optimization problems governed by such large-scale simulations.

The central question addressed by this workshop is: how do we
endow modern large-scale PDE solvers with optimization
capabilities?