An interior affine scaling projective algorithm for nonlinear equality and linear inequality constrained optimization (Q704177)

A trust region algorithm for solving minimization problems with nonlinear equality and linear inequality constraints but arbitrary smooth objective function is developed. Main features of the algorithm are the decomposition of the trust region subproblem into two simpler subproblems, the use of strictly feasible interior point techniques, the use of projective reduced Hessian matrices, affine scaling and non-monotone backtracking. The algorithm is weakly globally convergent, but conditions for strong global convergence and rate of local convergence are considered, too.