| Full text | |
| Author(s): |
Andreani, Roberto
;
Couto, Kelvin R.
;
Ferreira, Orizon P.
;
Haeser, Gabriel
Total Authors: 4
|
| Document type: | Journal article |
| Source: | SIAM JOURNAL ON OPTIMIZATION; v. 34, n. 2, p. 27-pg., 2024-01-01. |
| Abstract | |
In the past several years, augmented Lagrangian methods have been successfully applied to several classes of nonconvex optimization problems, inspiring new developments in both theory and practice. In this paper we bring most of these recent developments from nonlinear programming to the context of optimization on Riemannian manifolds, including equality and inequality constraints. Many research have been conducted on optimization problems on manifolds, however only recently the treatment of the constrained case has been considered. In this paper we propose to bridge this gap with respect to the most recent developments in nonlinear programming. In particular, we formulate several well-known constraint qualifications from the Euclidean context which are sufficient for guaranteeing global convergence of augmented Lagrangian methods, without requiring boundedness of the set of Lagrange multipliers. Convergence of the dual sequence can also be assured under a weak constraint qualification. The theory presented is based on so-called sequential optimality conditions, which is a powerful tool used in this context. The paper can also be read with the Euclidean context in mind, serving as a review of the most relevant constraint qualifications and global convergence theory of state-of-the-art augmented Lagrangian methods for nonlinear programming. (AU) | |
| FAPESP's process: | 17/17840-2 - Error estimation in nonlinear optimization |
| Grantee: | Leonardo Makoto Mito |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 23/08706-1 - Numerical optimization |
| Grantee: | Ernesto Julián Goldberg Birgin |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/18308-2 - Second-order optimality conditions and algorithms |
| Grantee: | Gabriel Haeser |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 18/24293-0 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |