A model-trust region algorithm utilizing a quadratic interpolant
This paper deals with a new procedure for solving unconstrained optimization problems arising for instance through minimization of the norm of the residual of a system of nonlinear equations. The author presents an improvement to the standard ``double dogleg'' version of this algorithm via replacement of its piecewise-linear approximant by a quadratic interpolant. This method is compared to the ``double dogleg'' strategy on a suite of standard test problems. These techniques are included in model-trust region algorithms.
scientific article; zbMATH DE number 1326408