Name
Abstract | ||
|---|---|---|
The goal of this paper is to show that the use of minimum Frobenius norm quadratic models can improve the performance of direct-search
methods. The approach taken here is to maintain the structure of directional direct-search methods, organized around a search
and a poll step, and to use the set of previously evaluated points generated during a direct-search run to build the models.
The minimization of the models within a trust region provides an enhanced search step. Our numerical results show that such
a procedure can lead to a significant improvement of direct search for smooth, piecewise smooth, and noisy problems. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10589-009-9283-0 | Computational Optimization and Applications |
Keywords | DocType | Volume |
Derivative-free optimization,Minimum Frobenius norm models,Direct search,Generalized pattern search,Search step,Data profiles | Journal | 46 |
Issue | ISSN | Citations |
2 | 0926-6003 | 39 |
PageRank | References | Authors |
1.45 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. L. Custódio | 1 | 152 | 8.09 |
| Humberto Rocha | 2 | 46 | 2.07 |
| luis n vicente | 3 | 176 | 11.24 |