| Full text | |
| Author(s): |
Birgin, E. G.
;
Martinez, J. M.
Total Authors: 2
|
| Document type: | Journal article |
| Source: | SIAM JOURNAL ON OPTIMIZATION; v. 27, n. 2, p. 1049-1074, 2017. |
| Web of Science Citations: | 10 |
| Abstract | |
Cubic-regularization and trust-region methods with worst-case first-order complexity O (epsilon (3/2)) and worst-case second-order complexity O (epsilon (3)) have been developed in the last few years. In this paper it is proved that the same complexities are achieved by means of a quadratic-regularization method with a cubic sufficient-descent condition instead of the more usual predicted-reduction based descent. Asymptotic convergence and order of convergence results are also presented. Finally, some numerical experiments comparing the new algorithm with a well-established quadratic regularization method are shown. (AU) | |
| 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 |
| FAPESP's process: | 13/05475-7 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 14/18711-3 - Mathematical modelling systems and decisions |
| Grantee: | José Mário Martinez Perez |
| Support Opportunities: | Research Grants - Visiting Researcher Grant - International |
| FAPESP's process: | 13/03447-6 - Combinatorial structures, optimization, and algorithms in theoretical Computer Science |
| Grantee: | Carlos Eduardo Ferreira |
| Support Opportunities: | Research Projects - Thematic Grants |