New constraint qualifications with second-order properties in nonlinear optimization (2020)
- Autores:
- Autor USP: HAESER, GABRIEL - IME
- Unidade: IME
- DOI: 10.1007/s10957-019-01603-x
- Assuntos: PROGRAMAÇÃO NÃO LINEAR; PROGRAMAÇÃO MATEMÁTICA
- Palavras-chave do autor: Nonlinear optimization; Constraint qualifications; Second-order optimality conditions
- Agências de fomento:
- Idioma: Inglês
- Imprenta:
- Fonte:
- Título: Journal of Optimization Theory and Applications
- ISSN: 0022-3239
- Volume/Número/Paginação/Ano: v. 184, p. 494-506, 2020
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
HAESER, Gabriel e RAMOS, A. New constraint qualifications with second-order properties in nonlinear optimization. Journal of Optimization Theory and Applications, v. 184, p. 494-506, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10957-019-01603-x. Acesso em: 09 out. 2024. -
APA
Haeser, G., & Ramos, A. (2020). New constraint qualifications with second-order properties in nonlinear optimization. Journal of Optimization Theory and Applications, 184, 494-506. doi:10.1007/s10957-019-01603-x -
NLM
Haeser G, Ramos A. New constraint qualifications with second-order properties in nonlinear optimization [Internet]. Journal of Optimization Theory and Applications. 2020 ; 184 494-506.[citado 2024 out. 09 ] Available from: https://doi.org/10.1007/s10957-019-01603-x -
Vancouver
Haeser G, Ramos A. New constraint qualifications with second-order properties in nonlinear optimization [Internet]. Journal of Optimization Theory and Applications. 2020 ; 184 494-506.[citado 2024 out. 09 ] Available from: https://doi.org/10.1007/s10957-019-01603-x - A note on linearly dependent symmetric matrices
- 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
- Optimality conditions and global convergence for nonlinear semidefinite programming
- A second-order optimality condition with first- and second-order complementarity associated with global convergence of algorithms
- Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary
- Towards an efficient augmented Lagrangian method for convex quadratic programming
- On second-order optimality conditions in nonlinear optimization
- On the constrained error bound condition and the projected Levenberg–Marquardt method
- On fuzzy uncertainties on the logistic equation
Informações sobre o DOI: 10.1007/s10957-019-01603-x (Fonte: oaDOI API)
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