Amaral, V. S.; Andreani, Roberto 
; Birgin, Ernesto Julian Goldberg ; Marcondes, Diaulas Murize Santana Vieira ; Martínez, José Mário
Fonte: Journal of Global Optimization. Unidade: IME
Assuntos: PROGRAMAÇÃO NÃO LINEAR, CÁLCULO DE VARIAÇÕES, CONTROLE ÓTIMO, MÉTODOS NUMÉRICOS, ANÁLISE NUMÉRICA, PESQUISA OPERACIONAL, CIÊNCIA DA COMPUTAÇÃO
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AMARAL, V. S. et al. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization. Journal of Global Optimization, v. 84, p. 527-561, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10898-022-01168-6. Acesso em: 30 set. 2024.APA
Amaral, V. S., Andreani, R., Birgin, E. J. G., Marcondes, D. M. S. V., & Martínez, J. M. (2022). On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization. Journal of Global Optimization, 84, 527-561. doi:10.1007/s10898-022-01168-6NLM
Amaral VS, Andreani R, Birgin EJG, Marcondes DMSV, Martínez JM. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization [Internet]. Journal of Global Optimization. 2022 ; 84 527-561.[citado 2024 set. 30 ] Available from: https://doi.org/10.1007/s10898-022-01168-6Vancouver
Amaral VS, Andreani R, Birgin EJG, Marcondes DMSV, Martínez JM. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization [Internet]. Journal of Global Optimization. 2022 ; 84 527-561.[citado 2024 set. 30 ] Available from: https://doi.org/10.1007/s10898-022-01168-6
