Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds (2024)
- Authors:
- Autor USP: HAESER, GABRIEL - IME
- Unidade: IME
- DOI: 10.1137/23M1582382
- Subjects: CÁLCULO DE VARIAÇÕES; CONTROLE ÓTIMO; ANÁLISE NUMÉRICA; PESQUISA OPERACIONAL; PROGRAMAÇÃO NÃO LINEAR
- Keywords: constraint qualifications; global convergence; augmented Lagrangian methods; Riemannian manifolds
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Philadelphia
- Date published: 2024
- Source:
- Título: SIAM Journal on Optimization
- ISSN: 1052-6234
- Volume/Número/Paginação/Ano: v. 34, n. 2, p. 1799-1825, 2024
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
ANDREANI, Roberto et al. Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds. SIAM Journal on Optimization, v. 34, n. 2, p. 1799-1825, 2024Tradução . . Disponível em: https://doi.org/10.1137/23M1582382. Acesso em: 01 out. 2024. -
APA
Andreani, R., Couto, K. R., Ferreira, O. P., & Haeser, G. (2024). Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds. SIAM Journal on Optimization, 34( 2), 1799-1825. doi:10.1137/23M1582382 -
NLM
Andreani R, Couto KR, Ferreira OP, Haeser G. Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds [Internet]. SIAM Journal on Optimization. 2024 ; 34( 2): 1799-1825.[citado 2024 out. 01 ] Available from: https://doi.org/10.1137/23M1582382 -
Vancouver
Andreani R, Couto KR, Ferreira OP, Haeser G. Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds [Internet]. SIAM Journal on Optimization. 2024 ; 34( 2): 1799-1825.[citado 2024 out. 01 ] Available from: https://doi.org/10.1137/23M1582382 - 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
- New constraint qualifications with second-order properties in nonlinear optimization
Informações sobre o DOI: 10.1137/23M1582382 (Fonte: oaDOI API)
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