On the global convergence of a general class of augmented Lagrangian methods (2025)
- Authors:
- USP affiliated authors: BIRGIN, ERNESTO JULIAN GOLDBERG - IME ; HAESER, GABRIEL - IME
- Unidade: IME
- DOI: 10.1007/s10957-025-02734-0
- Subjects: OTIMIZAÇÃO NÃO LINEAR; CONVERGÊNCIA; ALGORITMOS
- Keywords: Nonlinear optimization; Augmented Lagrangian methods; Convergence; Numerical experiments; Técnicas Lagrangianas aumentadas
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Optimization Theory and Applications
- ISSN: 0022-3239
- Volume/Número/Paginação/Ano: v. 206, art. 57, p. 1-25, 2025
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
BIRGIN, Ernesto Julian Goldberg et al. On the global convergence of a general class of augmented Lagrangian methods. Journal of Optimization Theory and Applications, v. 206, p. 1-25, 2025Tradução . . Disponível em: https://doi.org/10.1007/s10957-025-02734-0. Acesso em: 31 dez. 2025. -
APA
Birgin, E. J. G., Haeser, G., Maculan, N., & Ramirez, L. M. (2025). On the global convergence of a general class of augmented Lagrangian methods. Journal of Optimization Theory and Applications, 206, 1-25. doi:10.1007/s10957-025-02734-0 -
NLM
Birgin EJG, Haeser G, Maculan N, Ramirez LM. On the global convergence of a general class of augmented Lagrangian methods [Internet]. Journal of Optimization Theory and Applications. 2025 ; 206 1-25.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/s10957-025-02734-0 -
Vancouver
Birgin EJG, Haeser G, Maculan N, Ramirez LM. On the global convergence of a general class of augmented Lagrangian methods [Internet]. Journal of Optimization Theory and Applications. 2025 ; 206 1-25.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/s10957-025-02734-0 - Safeguarded augmented Lagrangian algorithms with scaled stopping criterion for the subproblems
- Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points
- Augmented Lagrangian for nonlinear SDPs applied to the covering problem
- Smoothing ℓ1-exact penalty method for intrinsically constrained Riemannian optimization problems
- An Augmented Lagrangian algorithm for nonlinear semidefinite programming applied to the covering problem
- Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds
- A relaxed quasinormality condition and the boundedness of dual augmented lagrangian sequences
- 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
Informações sobre o DOI: 10.1007/s10957-025-02734-0 (Fonte: oaDOI API)
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