A trust-region interior-point method for nonlinear programming

Authors:
Maria Cristina Villalobos;Yin Zhang
Affiliations:
University of Texas-Pan American, Edinburg, Texas;Rice University, Houston, Texas
Venue:
Proceedings of the 2005 conference on Diversity in computing
Year:
2005

Citing 4
Cited 0

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

Proceedings of the 2003 conference on Diversity in computing

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Abstract

Under mild conditions, the Jacobian associated with the Karush-Kuhn-Tucker (KKT) system of a (non-convex) nonlinear program is nonsingular near an isolated solution. However, this property may not hold away from such a solution. To enhance the robustness and efficiency of the primal-dual interior-point approach, we propose a method that at each iteration solves a trust-region, least-squares problem associated with the linearized perturbed KKT conditions. As a merit function, we use the Euclidean norm-square of the KKT conditions and provide a theoretical justification. We present some preliminary numerical results.