On the development of a trust region interior-point method for large scale nonlinear programs

Authors:
Miguel Argáez;Leticia Velázquez;Cristina Villalobos
Affiliations:
University of Texas-El Paso, El Paso, TX;University of Texas-El Paso, El Paso, TX;University of Texas-Pan American, Edinburg, TX
Venue:
Proceedings of the 2003 conference on Diversity in computing
Year:
2003

Citing 3
Cited 1

Trust region algorithms for optimization with nonlinear equality and inequality constraints

Trust region algorithms for optimization with nonlinear equality and inequality constraints
On the Implementation of an Algorithm for Large-Scale Equality Constrained Optimization

SIAM Journal on Optimization
On the global convergence of a modified augmented Lagrangian linesearch interior-point Newton method for nonlinear programming

Journal of Optimization Theory and Applications

A trust-region interior-point method for nonlinear programming

Proceedings of the 2005 conference on Diversity in computing

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Abstract

The focus of this paper is to present a new methodology for solving general nonlinear programs. We propose the use of interior-point methodology, trust-region globalization strategies, and conjugate gradient method to find a solution to large scale problems.