| Full text | |
| Author(s): |
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, Inst Math & Stat, Dept Comp Sci, Sao Paulo, SP - Brazil
[2] Univ Brasilia, Fac UnB Gama, Brasilia, DF - Brazil
[3] Univ Estadual Campinas, Inst Math Stat & Sci Comp, Dept Appl Math, Campinas, SP - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | Top; v. 29, n. 2 MAY 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
Many practical problems require the solution of large-scale constrained optimization problems for which preserving feasibility is a key issue, and the evaluation of the objective function is very expensive. In these cases it is mandatory to start with a feasible approximation of the solution, the obtention of which should not require objective function evaluations. The necessity of solving this type of problems motivated us to revisit the classical barrier approach for nonlinear optimization, providing a careful implementation of a modern version of this method. This is the main objective of the present paper. For completeness, we provide global convergence results and comparative numerical experiments with one of the state-of-the-art interior-point solvers for continuous optimization. (AU) | |
| FAPESP's process: | 12/05725-0 - Implementation of a software for large-scale minimization with linear constraints using trust-region methods |
| Grantee: | John Lenon Cardoso Gardenghi |
| Support Opportunities: | Scholarships in Brazil - Master |
| 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: | 18/24293-0 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support Opportunities: | Research Projects - Thematic Grants |