| Full text | |
| Author(s): |
Total Authors: 3
|
| Affiliation: | [1] Univ Sao Paulo, Inst Math Sci & Computat, Sao Carlos, SP - Brazil
[2] Univ Estadual Campinas, Dept Appl Math, Campinas, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS; v. 175, n. 1, p. 137-157, OCT 2017. |
| Web of Science Citations: | 1 |
| Abstract | |
The gradient sampling method is a recently developed tool for solving unconstrained nonsmooth optimization problems. Using just first-order information about the objective function, it generalizes the steepest descent method, one of the most classical methods for minimizing a smooth function. This study aims at determining under which circumstances one can expect the same local convergence result of the Cauchy method for the gradient sampling algorithm under the assumption that the problem is stated by a finite max-function around the optimal point. Additionally, at the end, we show how to practically accomplish the required hypotheses during the execution of the algorithm. (AU) | |
| FAPESP's process: | 13/05475-7 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support type: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | José Alberto Cuminato |
| Support type: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/22989-2 - A sampling method for constrained nonsmooth optimization problems |
| Grantee: | Lucas Eduardo Azevedo Simões |
| Support type: | Scholarships in Brazil - Post-Doctorate |
| FAPESP's process: | 13/14615-7 - On the nonmonotone line search in gradient sampling methods for nonconvex and nonsmooth optimization |
| Grantee: | Lucas Eduardo Azevedo Simões |
| Support type: | Scholarships in Brazil - Doctorate |