The smoothed-penalty algorithm for state constrained optimal control problems for partial differential equations

We present an algorithm for the solution of general inequality constrained optimization problems. The algorithm is based upon an exact penalty function that is approximated by a family of smooth functions. We present convergence results. As numerical examples we treat state constrained optimal control problems for elliptic partial differential equations. We compare the results with existing methods.