Global convergence of trust-region interior-point algorithms for infinite-dimensional nonconvex minimization subject to pointwise bounds

A class of interior-point trust-region algorithms for infinite-dimensional nonlinear optimization subject to pointwise bounds in L-p-Banach spaces, 2 less than or equal to p less than or equal to infinity, is formulated and a nalyzed. The problem formulation is motivated by optimal control problems w ith L-p-controls and pointwise control constraints. The interior-point trus t-region algorithms are generalizations of those recently introduced by Col eman and Li [SIAM J. Optim., 6 (1996), pp. 418-445] for finite-dimensional problems. Many of the generalizations derived in this paper are also import ant in the finite-dimensional context. All first- and second-order global c onvergence results known for trust-region methods in the finite-dimensional setting are extended to the infinite-dimensional framework of this paper.