Resumen

ARGAEZ, MIGUEL; HERNANDEZ, JAIME  y  VELAZQUEZ, LETICIA. An inexact Newton hybrid path-following algorithm for NLP. Rev.colomb.mat. [online]. 2007, vol.41, suppl.1, pp.197-220. ISSN 0034-7426.

In this paper we present a hybrid path-following algorithm that generates inexact Newton steps suited for solving large scale and/or degenerate nonlinear programs. The algorithm uses as a central region a relaxed notion of the central path, called quasicentral path, a generalized augmented Lagrangian function, weighted proximity measures, and a linesearch within a trust region strategy. We apply a semi-iterative method for obtaining inexact Newton steps by using the conjugate gradient algorithm as an iterative procedure. We present a numerical comparison, and some promising results are reported.

Palabras clave : Interior-point methods; trust region methods; linesearch technique; nonlinear programming; and conjugate gradient.

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