COMPUTATIONAL EXPERIENCE WITH QUADRATICALLY CONVERGENT MINIMIZATION METHODS

Abstract

A recently reported minimization method allows great flexibility in choosing successive steps without losing the property of quadratic convergence, but special precautions are necessary to ensure ultimate convergence from an arbitrary point for general functions. The paper makes an analysis of the required conditions, which give rise to several possible algorithms, and results of these for a number of problems are presented and discussed.