An interior point method for nonlinear optimization with a quasi-tangential subproblem
Optimization and Control
2015-09-10 v1
Abstract
In this paper, we proposed an interior point method for constrained optimization, which is characterized by the using of quasi-tangential subproblem. This algorithm follows the main ideas of primal dual interior point methods and Byrd-Omojokun's step decomposition strategy. The quasi-tangential subproblem is obtained by penalizing the null space constraint in the tangential subproblem. The resulted quasi-tangential step is not strictly lying in the null space of the gradients of constraints. We also use a line search trust-funnel-like strategy, instead of penalty function or filter technology, to globalize the method. Global convergence results were obtained under standard assumptions.
Cite
@article{arxiv.1509.02585,
title = {An interior point method for nonlinear optimization with a quasi-tangential subproblem},
author = {Songqiang Qiu and Zhongwen Chen},
journal= {arXiv preprint arXiv:1509.02585},
year = {2015}
}