Faculdade

Departamento

Marcos Raydan

Investigador Principal
43
10837

Interesses Científicos

My research interests include Numerical Analysis and Continuous Optimization, with a special focus on the development of algorithms for large-scale computations. The motivation for my current algorithmic and theoretical research comes from applications in data analysis.

Publicações Representativas

Full list at -----> https://orcid.org/0000-0003-0417-7981 Most recent ones: -------------------------------------------------------------------------------------------------------------------------------------------- - A hybrid direct search and projected simplex gradient method for convex constrained minimization, Optimization Methods and Software, Doi: 10.1080/10556788.2023.2263618 (2023), (with A. L. Custódio and E. Krulikovski). -------------------------------------------------------------------------------------------------------------------------------------------- - A low-cost alternating projection approach for a continuous formulation of convex and cardinality constrained optimization, Operations Research Forum, Doi: 10.1007/s43069-023-00257-w (2023), (with N. Krejic and E. Krulikovski). -------------------------------------------------------------------------------------------------------------------------------------------- - Derivative-free separable quadratic modeling and cubic regularization for unconstrained optimization, 4OR Q. J. Oper. Res., Doi: 10.1007/s10288-023-00541-9 (2023) (with A. L. Custódio and R. Garmanjani). ---------------------------------------------------------------------------------------------------------------------------------------- - The Max-Out Min-In Problem: a Tool for Data Analysis, Computers and Operations Research, Vol. 154, 106218, Doi: 10.1016/j.cor.2023.106218 (2023) (with J. Orestes Cerdeira and M. João Martins). ------------------------------------------------------------------------------------------------------------------------------------------ - An extended delayed weighted gradient algorithm for solving strongly convex nonquadratic optimization problems, Journal of Computational and Applied Mathematics, Vol. 416,114525, Doi: 10.1016/j.cam.2022.114525 (2022) (with Roberto Andreani, Harry Oviedo and Leonardo Secchin). ------------------------------------------------------------------------------------------------------------------------------------------ - Using first-order information in direct multisearch for multiobjective optimization, Optimization Methods and Software, Vol. 37(6), 2135-2156, Doi: 10.1080/10556788.2022.2060971 (2022) (with R. Andreani and A. L. Custódio). -------------------------------------------------------------------------------------------------------------------------------------------- - A family of optimal weighted conjugate-gradient-type methods for strictly convex quadratic minimization, Numerical Algorithms, Vol. 90, 1225-1252, Doi: 10.1007/s11075-021-01228-0 (2022) (with Roberto Andreani and Harry Oviedo).