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pro vyhledávání: '"E. A. Papa Quiroz"'
Publikováno v:
Annals of Operations Research
Annals of Operations Research, 2023, 321 (1), pp.451-467. ⟨10.1007/s10479-022-04725-0⟩
Annals of Operations Research, 2023, 321 (1), pp.451-467. ⟨10.1007/s10479-022-04725-0⟩
International audience; We present an inexact proximal point algorithm using quasi distances to solve a minimization problem in the Euclidean space. This algorithm is motivated by the proximal methods introduced by Attouch et al., section 4, (Math Pr
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b75cbae90edf3fcfb4d11ce5084e837
https://amu.hal.science/hal-03665851/document
https://amu.hal.science/hal-03665851/document
Publikováno v:
RAIRO - Operations Research. 52:159-176
In this paper we introduce an inexact proximal point algorithm using proximal distances for solving variational inequality problems when the mapping is pseudomonotone or quasimonotone. Under some natural assumptions we prove that the sequence generat
Autor:
E. A. Papa Quiroz
Publikováno v:
Journal of Global Optimization. 56:43-59
In this paper we present an extension of the proximal point algorithm with Bregman distances to solve constrained minimization problems with quasiconvex and convex objective function on Hadamard manifolds. The proposed algorithm is a modified and ext
Publikováno v:
Nonlinear Analysis: Theory, Methods & Applications. 75:5924-5932
In this paper we propose an extension of the proximal point method to solve minimization problems with quasiconvex locally Lipschitz objective functions on Hadamard manifolds. To reach this goal, we use the concept of Clarke subdifferential on Hadama
Autor:
E. A. Papa Quiroz, P. Roberto Oliveira
Publikováno v:
European Journal of Operational Research. 216:26-32
In this paper we propose an extension of proximal methods to solve minimization problems with quasiconvex objective functions on the nonnegative orthant. Assuming that the function is bounded from below and lower semicontinuous and using a general pr