Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization

摘要

A class of algorithms for unconstrained optimization is introduced, which subsumes the classical trust-region algorithm and two of its newer variants, as well as the cubic and quadratic regularization methods. A unified theory of global convergence to first-order critical points is then described for this class.