Zobrazeno 1 - 10
of 16
pro vyhledávání: '"J. C. O. Souza"'
Publikováno v:
Computational Optimization and Applications : an international journal, Vol. 84, p. 397-420 (2023)
Computational Optimization and Applications
Computational Optimization and Applications, 2023, 84 (2), pp.397-420. ⟨10.1007/s10589-022-00438-z⟩
Computational Optimization and Applications
Computational Optimization and Applications, 2023, 84 (2), pp.397-420. ⟨10.1007/s10589-022-00438-z⟩
International audience; In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd6e8a6589ada42838fd549b6310a6d8
https://hdl.handle.net/2078.1/272742
https://hdl.handle.net/2078.1/272742
Autor:
J. C. O. Souza, Pedro Jorge S. Santos
Publikováno v:
Optimization. 71:55-70
In this paper, we study the convergence of a proximal point method for solving quasi-equilibrium problems (QEP) in Hilbert spaces. We extent the method proposed by Moudafi [Proximal point algorithm...
Autor:
Sandro Dimy Barbosa Bitar, João Xavier da Cruz Neto, J. O. Lopes, J. C. O. Souza, Roberto Cristóvão Mesquita Silva
Publikováno v:
Optimization. 71:263-284
For solving constrained multiobjective problems with a vector-valued DC (difference of convex) objective function, we consider a vectorial Bregman regularized proximal point method which extends bo...
Autor:
Yldenilson Torres Almeida, João Xavier da Cruz Neto, J. C. O. Souza, Paulo Roberto de Oliveira
Publikováno v:
Computational Optimization and Applications. 76:649-673
We study the convergence of a modified proximal point method for DC functions in Hadamard manifolds. We use the iteration computed by the proximal point method for DC function extended to the Riemannian context by Souza and Oliveira (J Glob Optim 63:
Publikováno v:
Annals of Operations Research
Annals of Operations Research, 2020, 289 (2), pp.313-339. ⟨10.1007/s10479-018-3104-8⟩
Annals of Operations Research, Springer Verlag, 2020, 289 (2), pp.313-339
Annals of Operations Research, Springer Verlag, 2020, 289 (2), pp.313-339. ⟨10.1007/s10479-018-3104-8⟩
Annals of Operations Research, 2020, 289 (2), pp.313-339. ⟨10.1007/s10479-018-3104-8⟩
Annals of Operations Research, Springer Verlag, 2020, 289 (2), pp.313-339
Annals of Operations Research, Springer Verlag, 2020, 289 (2), pp.313-339. ⟨10.1007/s10479-018-3104-8⟩
International audience; The purpose of this paper is twofold. First, we examine convergence properties of an inexact proximal point method with a quasi distance as a regularization term in order to find a critical point (in the sense of Toland) of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ff01f4dd42e25e8934642c2feff9dd8
https://hal-amu.archives-ouvertes.fr/hal-01985336/document
https://hal-amu.archives-ouvertes.fr/hal-01985336/document
Autor:
João Xavier da Cruz Neto, Glaydston de Carvalho Bento, Paulo Roberto de Oliveira, Sandro Dimy Barbosa Bitar, J. C. O. Souza
Publikováno v:
Journal of Optimization Theory and Applications. 183:977-992
In this paper, we perform the steepest descent method for computing Riemannian center of mass on Hadamard manifolds. To this end, we extend convergence of the method to the Hadamard setting for continuously differentiable (possible nonconvex) functio
Publikováno v:
Optimization Letters. 13:1143-1155
In this paper, we propose a Bregman regularized proximal point method for solving monotone equilibrium problems. Existence and uniqueness results as well as convergence of the sequence to a solution of an equilibrium problem is analyzed. We assume a
Autor:
Sandro Dimy Barbosa Bitar, João Xavier da Cruz Neto, Glaydston de Carvalho Bento, J. C. O. Souza, Antoine Soubeyran
Publikováno v:
Computational Optimization and Applications
Computational Optimization and Applications, Springer Verlag, 2020, 75 (1), pp.263-290. ⟨10.1007/s10589-019-00139-0⟩
Computational Optimization and Applications, 2020, 75 (1), pp.263-290. ⟨10.1007/s10589-019-00139-0⟩
Computational Optimization and Applications, Springer Verlag, 2020, 75 (1), pp.263-290. ⟨10.1007/s10589-019-00139-0⟩
Computational Optimization and Applications, 2020, 75 (1), pp.263-290. ⟨10.1007/s10589-019-00139-0⟩
International audience; We consider the constrained multi-objective optimization problem of finding Pareto critical points of difference of convex functions. The new approach proposed by Bento et al. (SIAM J Optim 28:1104–1120, 2018) to study the c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9acb6eed5a544b2f2f906e1f480298e
https://hal-amu.archives-ouvertes.fr/hal-02351104/document
https://hal-amu.archives-ouvertes.fr/hal-02351104/document
Autor:
J. C. O. Souza
Publikováno v:
Journal of Optimization Theory and Applications. 179:745-760
We study the convergence of exact and inexact versions of the proximal point method with a generalized regularization function in Hadamard manifolds for solving scalar and vectorial optimization problems involving Lipschitz functions. We consider a l
Publikováno v:
Optimization. 68:1305-1319
We present an interior proximal method for solving constrained nonconvex optimization problems where the objective function is given by the difference of two convex function (DC function). ...