Minimization of nonlinear functionals on infinite dimensional spaces subject to constraints. Solution algorithms for constrained and unconstrained nonlinear optimization problems. Aspects of numerical approximation and implementation. Convex optimization. Nonsmooth optimization.
Existence and uniqueness of solutions. Necessary and sufficient optimality conditions. Constraint qualifications. Kuhn-Tucker theorems. Steepest descent and Newton-type methods for unconstrained optimization, SQP methods, penalty methods and interior point methods for constrained optimization. Semismooth Newton and Primal-Dual Active set methods for nonsmooth problems.