J
José Mario Martínez
Researcher at State University of Campinas
Publications - 265
Citations - 16883
José Mario Martínez is an academic researcher from State University of Campinas. The author has contributed to research in topics: Nonlinear programming & Constrained optimization. The author has an hindex of 51, co-authored 263 publications receiving 14041 citations. Previous affiliations of José Mario Martínez include Spanish National Research Council & Universidad del Desarrollo.
Papers
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Journal ArticleDOI
Evaluation complexity for nonlinear constrained optimization using unscaled kkt conditions and high-order models
Ernesto G. Birgin,John Lenon Cardoso Gardenghi,José Mario Martínez,Sandra A. Santos,Ph. L. Toint +4 more
TL;DR: The evaluation complexity of general nonlinear, possibly nonconvex, constrained optimization is analyzed and it is shown that an $\epsilon$-approximate first-order critical point of the problem can be computed in order of O(p-2(p+1)/p), using a two-phase algorithm inspired by Cartis, Gould, and Toint.
Book ChapterDOI
A Box-Constrained Optimization Algorithm with Negative Curvature Directions and Spectral Projected Gradients
TL;DR: A practical algorithm for box-constrained optimization that combines an active-set strategy with spectral projected gradient iterations and a strategy that deals efficiently with negative curvature is introduced.
Journal ArticleDOI
A derivative-free nonmonotone line-search technique for unconstrained optimization
TL;DR: In this article, a tolerant derivative-free nonmonotone line search technique is proposed and analyzed for unconstrained minimization of the objective function and non-escent directions.
Journal ArticleDOI
Local Convergence of an Inexact-Restoration Method and Numerical Experiments
TL;DR: In this paper, local convergence of inexact-restoration methods for nonlinear programming is proved and numerical experiments are performed with the objective of evaluating the behavior of the purely local method against a globally convergent non-linear programming algorithm.
Journal ArticleDOI
Optimization techniques for the estimation of the thickness and the optical parameters of thin films using reflectance data
TL;DR: In this article, the authors considered the problem of estimating the thickness and the optical constants (extinction coefficient and refractive index) of thin films from the spectrum of normal reflectance R. This is an ill-conditioned highly underdetermined inverse problem.