Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/11216
Title: | Incorporating minimum Frobenius norm models in direct search | Authors: | Custódio, Ana Luísa Rocha, Humberto Vicente, Luís Nunes |
Keywords: | Derivative-free optimization; Minimum Frobenius norm models; Direct search; Generalized pattern search; Search step; Data profiles | Issue Date: | 2008 | Publisher: | Centro de Matemática da Universidade de Coimbra | Citation: | Pré-Publicações DMUC. 08-51 (2008) | 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 stochastic and nonstochastic noisy problems. | URI: | https://hdl.handle.net/10316/11216 | Rights: | openAccess |
Appears in Collections: | FCTUC Matemática - Vários |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Incorporating minimum Frobenius norm models in direct search.pdf | 546.24 kB | Adobe PDF | View/Open |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.