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:
- Language: Inglês
- Imprenta:
- Source:
- Título: 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: 24 dez. 2025. -
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 2025 dez. 24 ] 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 2025 dez. 24 ] Available from: https://doi.org/10.1007/s10589-021-00281-8 - A second-order optimality condition with first- and second-order complementarity associated with global convergence of algorithms
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- A relaxed quasinormality condition and the boundedness of dual augmented lagrangian sequences
- On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods
- Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds
- A note on linearly dependent symmetric matrices
- Optimality conditions and global convergence for nonlinear semidefinite programming
- Condições de otimalidade e algoritmos em otimização não linear
- Convergence detection for optimization algorithms: approximate-KKT stopping criterion when Lagrange multipliers are not available
- Optimality conditions for nonlinear second-order cone programming and symmetric cone programming
Informações sobre o DOI: 10.1007/s10589-021-00281-8 (Fonte: oaDOI API)
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