PDE Constrained Optimization
Optimization problems governed by partial differential equations (PDEs) arise in a growing number of science and engineering applications in the context of optimal control, optimal design, or parameter identification. The robust and efficient solution of these problems presents many challenges arising from the interactions among application specific structure, infinite dimensional problem structure, discretization, numerical solution of the underlying PDE, and numerical optimization.
In this talk I will discuss the design, theory and application of derivative based optimization algorithms for the solution of PDE constrained optimization problems. I will discuss the interaction between the infinite dimensional problem structure, discretization of the PDEs, and optimization algorithms and I will highlight algorithmic developments that were motivated by the PDE constraints.
Matthias Heinkenschloss, Rice University
