  The Polyhedral Active Set Algorithm (PASA) is designed to optimize a general
nonlinear function over a polyhedron. Phase one of the algorithm is a
nonmonotone gradient projection algorithm, while phase two is an active set
algorithm that explores faces of the constraint polyhedron. A gradient-based
implementation is presented, where a projected version of the conjugate
gradient algorithm is employed in phase two. Asymptotically, only phase two is
performed. Comparisons are given with IPOPT using polyhedral constrained
problems from CUTEst and the Maros/Meszaros quadratic programming test set.
