Spectral-scaling quasi-Newton methods with updates from the one parameter of the Broyden family
The authors consider the unconstrained optimization problem \[ \min f(x),\quad x\in\mathbb{R}^n, \] and propose spectral-scaling one parameter Broyden family methods which allow for negative values of the parameter. It is shown that the proposed methods possess some good properties such as quadratic termination property and single-step convergence rate not inferior to that of the steepest descent method when minimizing an \(n\)-dimensional quadratic function. Numerical examples are given.
scientific article; zbMATH DE number 6155456