On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming (2021)
- Authors:
- Autor USP: HAESER, GABRIEL - IME
- Unidade: IME
- DOI: 10.1007/s10589-021-00281-8
- Subjects: PROGRAMAÇÃO NÃO LINEAR; PROGRAMAÇÃO MATEMÁTICA; MÉTODOS NUMÉRICOS
- Keywords: Nonlinear semidefnite programming; Symmetric cones; Optimality conditions; Constraint qualifcations; Augmented Lagrangian method
- Agências de fomento:
- Financiado pela Japan Society for thePromotion of Science
- Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Processo FAPESP: 2018/24293-0 - Financiado pela FAPES
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
- Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Computational Optimization and Applications
- ISSN: 0926-6003
- Volume/Número/Paginação/Ano: v. 79, p. 633-648, 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
ANDREANI, Roberto et al. On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming. Computational Optimization and Applications, v. 79, p. 633-648, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10589-021-00281-8. Acesso em: 19 set. 2024. -
APA
Andreani, R., Fukuda, E. H., Haeser, G., Santos, D. O., & Secchin, L. D. (2021). On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming. Computational Optimization and Applications, 79, 633-648. doi:10.1007/s10589-021-00281-8 -
NLM
Andreani R, Fukuda EH, Haeser G, Santos DO, Secchin LD. On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming [Internet]. Computational Optimization and Applications. 2021 ; 79 633-648.[citado 2024 set. 19 ] Available from: https://doi.org/10.1007/s10589-021-00281-8 -
Vancouver
Andreani R, Fukuda EH, Haeser G, Santos DO, Secchin LD. On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming [Internet]. Computational Optimization and Applications. 2021 ; 79 633-648.[citado 2024 set. 19 ] Available from: https://doi.org/10.1007/s10589-021-00281-8 - Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds
- A note on linearly dependent symmetric matrices
- Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary
- A second-order optimality condition with first- and second-order complementarity associated with global convergence of algorithms
- Optimality conditions and global convergence for nonlinear semidefinite programming
- On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods
- On the constrained error bound condition and the projected Levenberg–Marquardt method
- On second-order optimality conditions in nonlinear optimization
- Towards an efficient augmented Lagrangian method for convex quadratic programming
- On a conjecture in second-order optimality conditions
Informações sobre o DOI: 10.1007/s10589-021-00281-8 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 | 3036024.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
