English

Sequential constant rank constraint qualifications for nonlinear semidefinite programming with applications

Optimization and Control 2021-06-08 v2

Abstract

We present new constraint qualification conditions for nonlinear semidefinite programming that extend some of the constant rank-type conditions from nonlinear programming. As an application of these conditions, we provide a unified global convergence proof of a class of algorithms to stationary points without assuming neither uniqueness of the Lagrange multiplier nor boundedness of the Lagrange multipliers set. This class of algorithm includes, for instance, general forms of augmented Lagrangian, sequential quadratic programming, and interior point methods. We also compare these new conditions with some of the existing ones, including the nondegeneracy condition, Robinson's constraint qualification, and the metric subregularity constraint qualification.

Keywords

Cite

@article{arxiv.2106.00775,
  title  = {Sequential constant rank constraint qualifications for nonlinear semidefinite programming with applications},
  author = {Roberto Andreani and Gabriel Haeser and Leonardo M. Mito and Héctor Ramírez C},
  journal= {arXiv preprint arXiv:2106.00775},
  year   = {2021}
}

Comments

19 pages, trimmed

R2 v1 2026-06-24T02:43:38.325Z