A modified augmented Lagrangian merit function, and Q-superlinear characterization results for primal-dual Quasi-Newton interior-point method for nonlinear programming

Two classes of primal-dual interior-point methods for nonlinear programming are studied. The first class corresponds to a path-following Newton method formulated in terms of the nonnegative variables rather than all primal and dual variables. The centrality condition is a relaxation of the perturbed Karush-Kuhn-Tucker condition and primarily forces feasibility in the constraints. In order to globalize the method using a linesearch strategy, a modified augmented Lagrangian merit function is defined in terms of the centrality condition. The second class is the Quasi-Newton interior-point methods. In this class the well known Boggs-Tolle-Wang characterization of Q-superlinear convergence for Quasi-Newton method for equality constrained optimization is extended. Critical issues in this extension are; the choice of the centering parameter, the choice of the steplength parameter, and the choice of the primary variables.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Engineering

Grantor

Rice University

Year dc:date.issued

1997

Author dc:creator

• Paroda Garcia, Zeferino

Advisor dc:contributor.advisor

• Tapia, Richard A.

• Mathematics
• Operations research
• Computer science

Statement dc:rights

• Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1911/19195

OAI identifier oai:identifier

oai:repository.rice.edu:1911/19195