| Full text | |
| Author(s): |
Total Authors: 3
|
| Affiliation: | [1] Univ Estadual Campinas, Dept Appl Math, Campinas, SP - Brazil
[2] Univ Sao Paulo, Dept Appl Math, Sao Paulo, SP - Brazil
[3] Univ Fed Acre, Ctr Exact & Technol Sci, Rio Branco, AC - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | MATHEMATICAL PROGRAMMING; v. 180, n. 1-2, p. 203-235, MAR 2020. |
| Web of Science Citations: | 1 |
| Abstract | |
Sequential optimality conditions have played a major role in unifying and extending global convergence results for several classes of algorithms for general nonlinear optimization. In this paper, we extend theses concepts for nonlinear semidefinite programming. We define two sequential optimality conditions for nonlinear semidefinite programming. The first is a natural extension of the so-called Approximate-Karush-Kuhn-Tucker (AKKT), well known in nonlinear optimization. The second one, called Trace-AKKT, is more natural in the context of semidefinite programming as the computation of eigenvalues is avoided. We propose an augmented Lagrangian algorithm that generates these types of sequences and new constraint qualifications are proposed, weaker than previously considered ones, which are sufficient for the global convergence of the algorithm to a stationary point. (AU) | |
| FAPESP's process: | 17/18308-2 - Second-order optimality conditions and algorithms |
| Grantee: | Gabriel Haeser |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 13/05475-7 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support Opportunities: | Research Projects - Thematic Grants |