Abstract
An algorithm for unconstrained minimization is proposed which is invariant to a non-linear scaling of a strictly convex quadratic function and which generates mutually conjugate directions for extended quadratic function. It is derived for inexact line searches and is designed for general use, it compares favorably numerical tests [over eight test functions and dimensionally up to (2-100) with the H/S, DX, F/R, P/R, and A/B algorithms on which this new algorithm is based.
