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Artigo de periodico
On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming (2021)
Andreani, Roberto ; Fukuda, Ellen Hidemi ; Haeser, Gabriel ; Santos, D. O.; Secchin, Leornardo Delarmelina
Source: Computational Optimization and Applications. Unidade: IME
Subjects: PROGRAMAÇÃO NÃO LINEAR, PROGRAMAÇÃO MATEMÁTICA, MÉTODOS NUMÉRICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 06 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. 06 ] 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. 06 ] Available from: https://doi.org/10.1007/s10589-021-00281-8
Trabalho de evento-anais periodico
An Augmented Lagrangian method for quasi-equilibrium problems (2020)
Bueno, L. F; Haeser, Gabriel ; Lara, F; Rojas, Frank Navarro
Source: Computational Optimization and Applications. Conference titles: Brazilian Workshop on Continuous Optimization. Unidade: IME
Assunto: PROGRAMAÇÃO MATEMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BUENO, L. F et al. An Augmented Lagrangian method for quasi-equilibrium problems. Computational Optimization and Applications. New York: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s10589-020-00180-4. Acesso em: 06 dez. 2025. , 2020
APA
Bueno, L. F., Haeser, G., Lara, F., & Rojas, F. N. (2020). An Augmented Lagrangian method for quasi-equilibrium problems. Computational Optimization and Applications. New York: Instituto de Matemática e Estatística, Universidade de São Paulo. doi:10.1007/s10589-020-00180-4
NLM
Bueno LF, Haeser G, Lara F, Rojas FN. An Augmented Lagrangian method for quasi-equilibrium problems [Internet]. Computational Optimization and Applications. 2020 ; 76( 3): 737-766.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-020-00180-4
Vancouver
Bueno LF, Haeser G, Lara F, Rojas FN. An Augmented Lagrangian method for quasi-equilibrium problems [Internet]. Computational Optimization and Applications. 2020 ; 76( 3): 737-766.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-020-00180-4
Trabalho de evento-anais periodico
Towards an efficient augmented Lagrangian method for convex quadratic programming (2020)
Bueno, Luís Felipe ; Haeser, Gabriel ; Santos, Luiz-Rafael
Source: Computational Optimization and Applications. Conference titles: Brazilian Workshop on Continuous Optimization. Unidade: IME
Assunto: PROGRAMAÇÃO MATEMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BUENO, Luís Felipe e HAESER, Gabriel e SANTOS, Luiz-Rafael. Towards an efficient augmented Lagrangian method for convex quadratic programming. Computational Optimization and Applications. New York: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s10589-019-00161-2. Acesso em: 06 dez. 2025. , 2020
APA
Bueno, L. F., Haeser, G., & Santos, L. -R. (2020). Towards an efficient augmented Lagrangian method for convex quadratic programming. Computational Optimization and Applications. New York: Instituto de Matemática e Estatística, Universidade de São Paulo. doi:10.1007/s10589-019-00161-2
NLM
Bueno LF, Haeser G, Santos L-R. Towards an efficient augmented Lagrangian method for convex quadratic programming [Internet]. Computational Optimization and Applications. 2020 ; 76( 3): 767-800.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-019-00161-2
Vancouver
Bueno LF, Haeser G, Santos L-R. Towards an efficient augmented Lagrangian method for convex quadratic programming [Internet]. Computational Optimization and Applications. 2020 ; 76( 3): 767-800.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-019-00161-2
Artigo de periodico
A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization (2019)
Birgin, Ernesto Julian Goldberg ; Martinez, José Mario
Source: Computational Optimization and Applications. Unidade: IME
Subjects: OTIMIZAÇÃO MATEMÁTICA, PROGRAMAÇÃO MATEMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e MARTINEZ, José Mario. A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization. Computational Optimization and Applications, v. 73, n. 3, p. 707-753, 2019Tradução . . Disponível em: https://doi.org/10.1007/s10589-019-00089-7. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., & Martinez, J. M. (2019). A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization. Computational Optimization and Applications, 73( 3), 707-753. doi:10.1007/s10589-019-00089-7
NLM
Birgin EJG, Martinez JM. A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization [Internet]. Computational Optimization and Applications. 2019 ; 73( 3): 707-753.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-019-00089-7
Vancouver
Birgin EJG, Martinez JM. A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization [Internet]. Computational Optimization and Applications. 2019 ; 73( 3): 707-753.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-019-00089-7
Artigo de periodico
A fast gradient and function sampling method for finite-max functions (2018)
Helou, Elias Salomão ; Santos, Sandra A.; Simões, Lucas E. A.
Source: Computational Optimization and Applications. Unidade: ICMC
Subjects: FUNÇÕES ESPECIAIS, APROXIMAÇÃO, MÉTODOS NUMÉRICOS DE OTIMIZAÇÃO, MÉTODOS ITERATIVOS, OTIMIZAÇÃO MATEMÁTICA, OTIMIZAÇÃO GLOBAL, OTIMIZAÇÃO IRRESTRITA, OTIMIZAÇÃO CONVEXA, OTIMIZAÇÃO ESTOCÁSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HELOU, Elias Salomão e SANTOS, Sandra A. e SIMÕES, Lucas E. A. A fast gradient and function sampling method for finite-max functions. Computational Optimization and Applications, v. 71, n. 3, p. 673-717, 2018Tradução . . Disponível em: https://doi.org/10.1007/s10589-018-0030-2. Acesso em: 06 dez. 2025.
APA
Helou, E. S., Santos, S. A., & Simões, L. E. A. (2018). A fast gradient and function sampling method for finite-max functions. Computational Optimization and Applications, 71( 3), 673-717. doi:10.1007/s10589-018-0030-2
NLM
Helou ES, Santos SA, Simões LEA. A fast gradient and function sampling method for finite-max functions [Internet]. Computational Optimization and Applications. 2018 ; 71( 3): 673-717.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-018-0030-2
Vancouver
Helou ES, Santos SA, Simões LEA. A fast gradient and function sampling method for finite-max functions [Internet]. Computational Optimization and Applications. 2018 ; 71( 3): 673-717.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-018-0030-2
Artigo de periodico
Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points (2018)
Birgin, Ernesto Julian Goldberg ; Haeser, Gabriel ; Ramos, Alberto
Source: Computational Optimization and Applications. Unidade: IME
Assunto: PROGRAMAÇÃO NÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e HAESER, Gabriel e RAMOS, Alberto. Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points. Computational Optimization and Applications, v. 69, n. 1, p. 51–75, 2018Tradução . . Disponível em: https://doi.org/10.1007/s10589-017-9937-2. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., Haeser, G., & Ramos, A. (2018). Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points. Computational Optimization and Applications, 69( 1), 51–75. doi:10.1007/s10589-017-9937-2
NLM
Birgin EJG, Haeser G, Ramos A. Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points [Internet]. Computational Optimization and Applications. 2018 ; 69( 1): 51–75.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-017-9937-2
Vancouver
Birgin EJG, Haeser G, Ramos A. Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points [Internet]. Computational Optimization and Applications. 2018 ; 69( 1): 51–75.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-017-9937-2
Artigo de periodico
Sequential equality-constrained optimization for nonlinear programming (2016)
Birgin, Ernesto Julian Goldberg ; Bueno, L. F; Martinez, José Mario
Source: Computational Optimization and Applications. Unidade: IME
Subjects: PROGRAMAÇÃO NÃO LINEAR, OTIMIZAÇÃO MATEMÁTICA, PESQUISA OPERACIONAL, PROGRAMAÇÃO MATEMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e BUENO, L. F e MARTINEZ, José Mario. Sequential equality-constrained optimization for nonlinear programming. Computational Optimization and Applications, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10589-016-9849-6. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., Bueno, L. F., & Martinez, J. M. (2016). Sequential equality-constrained optimization for nonlinear programming. Computational Optimization and Applications. doi:10.1007/s10589-016-9849-6
NLM
Birgin EJG, Bueno LF, Martinez JM. Sequential equality-constrained optimization for nonlinear programming [Internet]. Computational Optimization and Applications. 2016 ;[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-016-9849-6
Vancouver
Birgin EJG, Bueno LF, Martinez JM. Sequential equality-constrained optimization for nonlinear programming [Internet]. Computational Optimization and Applications. 2016 ;[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-016-9849-6
Artigo de periodico
Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization (2012)
Birgin, Ernesto Julian Goldberg ; Martinez, J. M
Source: Computational Optimization and Applications. Unidade: IME
Assunto: PROGRAMAÇÃO NÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e MARTINEZ, J. M. Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization. Computational Optimization and Applications, v. 51, n. 3, p. 941-965, 2012Tradução . . Disponível em: https://doi.org/10.1007/s10589-011-9396-0. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., & Martinez, J. M. (2012). Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization. Computational Optimization and Applications, 51( 3), 941-965. doi:10.1007/s10589-011-9396-0
NLM
Birgin EJG, Martinez JM. Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization [Internet]. Computational Optimization and Applications. 2012 ; 51( 3): 941-965.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-011-9396-0
Vancouver
Birgin EJG, Martinez JM. Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization [Internet]. Computational Optimization and Applications. 2012 ; 51( 3): 941-965.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-011-9396-0
Artigo de periodico
Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization (2008)
Birgin, Ernesto Julian Goldberg ; Martínez, José Mário
Source: Computational Optimization and Applications. Unidade: IME
Assunto: PROGRAMAÇÃO NÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e MARTÍNEZ, José Mário. Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization. Computational Optimization and Applications, v. 39, n. 1, p. 1-16, 2008Tradução . . Disponível em: https://doi.org/10.1007/s10589-007-9050-z. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., & Martínez, J. M. (2008). Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization. Computational Optimization and Applications, 39( 1), 1-16. doi:10.1007/s10589-007-9050-z
NLM
Birgin EJG, Martínez JM. Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization [Internet]. Computational Optimization and Applications. 2008 ; 39( 1): 1-16.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-007-9050-z
Vancouver
Birgin EJG, Martínez JM. Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization [Internet]. Computational Optimization and Applications. 2008 ; 39( 1): 1-16.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-007-9050-z
Artigo de periodico
Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems (2005)
Birgin, Ernesto Julian Goldberg ; Castillo, Romulo A; Martinez, Jesus Manuel
Source: Computational Optimization and Applications. Unidade: IME
Assunto: PROGRAMAÇÃO NÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e CASTILLO, Romulo A e MARTINEZ, Jesus Manuel. Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems. Computational Optimization and Applications, v. 31, n. 1, p. 31-55, 2005Tradução . . Disponível em: https://doi.org/10.1007/s10589-005-1066-7. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., Castillo, R. A., & Martinez, J. M. (2005). Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems. Computational Optimization and Applications, 31( 1), 31-55. doi:10.1007/s10589-005-1066-7
NLM
Birgin EJG, Castillo RA, Martinez JM. Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems [Internet]. Computational Optimization and Applications. 2005 ; 31( 1): 31-55.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-005-1066-7
Vancouver
Birgin EJG, Castillo RA, Martinez JM. Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems [Internet]. Computational Optimization and Applications. 2005 ; 31( 1): 31-55.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1007/s10589-005-1066-7
Artigo de periodico
Large-scale active-set box-constrained optimization method with spectral projected gradients (2002)
Birgin, Ernesto Julian Goldberg ; Martínez, José Mário
Source: Computational Optimization and Applications. Unidade: IME
Assunto: MÉTODOS NUMÉRICOS DE OTIMIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIRGIN, Ernesto Julian Goldberg e MARTÍNEZ, José Mário. Large-scale active-set box-constrained optimization method with spectral projected gradients. Computational Optimization and Applications, v. 23, n. 1, p. 101-125, 2002Tradução . . Disponível em: https://doi.org/10.1023/A:1019928808826. Acesso em: 06 dez. 2025.
APA
Birgin, E. J. G., & Martínez, J. M. (2002). Large-scale active-set box-constrained optimization method with spectral projected gradients. Computational Optimization and Applications, 23( 1), 101-125. doi:10.1023/A:1019928808826
NLM
Birgin EJG, Martínez JM. Large-scale active-set box-constrained optimization method with spectral projected gradients [Internet]. Computational Optimization and Applications. 2002 ; 23( 1): 101-125.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1023/A:1019928808826
Vancouver
Birgin EJG, Martínez JM. Large-scale active-set box-constrained optimization method with spectral projected gradients [Internet]. Computational Optimization and Applications. 2002 ; 23( 1): 101-125.[citado 2025 dez. 06 ] Available from: https://doi.org/10.1023/A:1019928808826

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