Research Grants 23/08706-1 - Otimização contínua, Algoritmos - BV FAPESP
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Numerical optimization

Grant number: 23/08706-1
Support Opportunities:Research Projects - Thematic Grants
Start date: August 01, 2024
End date: July 31, 2029
Field of knowledge:Physical Sciences and Mathematics - Mathematics - Applied Mathematics
Principal Investigator:Ernesto Julián Goldberg Birgin
Grantee:Ernesto Julián Goldberg Birgin
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Pesquisadores principais:
Carlile Campos Lavor ; Gabriel Haeser ; José Mário Martinez Perez ; Paulo José da Silva e Silva ; Roberto Andreani
Associated researchers:Daiana Oliveira dos Santos ; Francisco de Assis Magalhães Gomes Neto ; Leandro Martinez ; Luis Felipe Cesar da Rocha Bueno ; Luiz Leduíno de Salles Neto ; Thadeu Alves Senne ; Thiago Siqueira Santos ; Tiara Martini dos Santos
Associated research grant(s):24/12967-8 - Modern optimization techniques applied to hyperparameter tuning and distance geometry, AV.BR
Associated scholarship(s):24/22641-2 - Acceleration of proximal gradiente methods, BP.PD
24/21786-7 - Computational Methods Applied to Bio-molecular Structure Determination from the Perspective of Distance Geometry, BP.PD
24/22723-9 - Properties of algorithms for constrained optimization, BP.PD
+ associated scholarships 24/22384-0 - Implementation of augmented Lagrangian methods with first-order information, BP.PD
25/00034-0 - Nash Equilibrium Problems with Descent Information, BP.DD
24/20168-8 - Second-order methods for discontinuous composite problems, BP.DR
24/21317-7 - Constraint qualifications for conic optimization, BP.DD
24/21644-8 - DC optimization for machine learning and data science, BP.DD
24/21718-1 - Scheduling problems with a cost function aligned with current concerns about sustainability and the environment, BP.DD - associated scholarships

Abstract

This project deals with theoretical, computational and application aspects of Optimization. The project aims at the development, theoretical analysis, implementation and application of algorithms for different aspects of Optimization, with emphasis on Continuous Optimization. The project relies on applications with which the team is familiar. Emphasis is placed on algorithms with a solid theoretical background, which involves precise characterization of the problems addressed, with careful and competitive computational implementation, and connections to Engineering and Applied Sciences. The project team has been active in the Brazilian scientific environment for over 40 years, and is sensitive to new trends and modern applications of Optimization. Over the years, the team has made significant contributions in areas involving decomposition methods, quasi-Newton methods, sequential quadratic programming, Augmented Lagrangian methods, Inexact Restoration, large problems, sequential optimality conditions, derivative-free minimization, algorithmic complexity, image reconstruction and machine learning, among others. The experience accumulated, as well as the incorporation and renewal of the research team in the project, enables the team to tackle problems in which the objective function is difficult, impossible to evaluate, or of questionable existence, the number of variables is enormous or unknown, and finally, the uncertainty extends to the constraints. Addressing these problems necessarily requires interdisciplinary approaches, and the desired impact is scientific, economic, and social at the same time. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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Scientific publications (8)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BIRGIN, ERNESTO G.; GARDENGHI, JOHN L.; MARCONDES, DIAULAS S.; MARTINEZ, JOSE MARIO. Accelerated derivative-free spectral residual method for nonlinear systems of equations. RAIRO-OPERATIONS RESEARCH, v. 59, n. 1, p. 16-pg., . (23/08706-1, 22/05803-3, 13/07375-0)
BIRGIN, ERNESTO G.; LAURAIN, ANTOINE; SOUZA, DANILO R.. Reconstruction of Voronoi diagrams in inverse potential problems. ESAIM-CONTROL OPTIMISATION AND CALCULUS OF VARIATIONS, v. 30, p. 37-pg., . (22/05803-3, 22/16733-6, 13/07375-0, 23/08706-1)
MARQUES, ROMULO S.; SOUZA, MICHAEL; BATISTA, FERNANDO; GONCALVES, MIGUEL; LAVOR, CARLILE. A Probabilistic Approach in the Search Space of the Molecular Distance Geometry Problem. JOURNAL OF CHEMICAL INFORMATION AND MODELING, v. N/A, p. 8-pg., . (13/07375-0, 23/08706-1)
ALVAREZ, G. Q.; BIRGIN, E. G.. A first-order regularized approach to the order-value optimization problem. OPTIMIZATION METHODS & SOFTWARE, v. N/A, p. 25-pg., . (23/08706-1, 22/05803-3, 13/07375-0)
ANDREANI, ROBERTO; RAMOS, ALBERTO; SECCHIN, LEONARDO D.. IMPROVING THE GLOBAL CONVERGENCE OF INEXACT RESTORATION METHODS FOR CONSTRAINED OPTIMIZATION PROBLEMS\ast. SIAM JOURNAL ON OPTIMIZATION, v. 34, n. 4, p. 27-pg., . (13/07375-0, 17/18308-2, 18/24293-0, 23/08706-1)
ANDREANI, ROBERTO; COUTO, KELVIN R.; FERREIRA, ORIZON P.; HAESER, GABRIEL. CONSTRAINT QUALIFICATIONS AND STRONG GLOBAL CONVERGENCE PROPERTIES OF AN AUGMENTED LAGRANGIAN METHOD ON RIEMANNIAN MANIFOLDS. SIAM JOURNAL ON OPTIMIZATION, v. 34, n. 2, p. 27-pg., . (17/17840-2, 23/08706-1, 17/18308-2, 18/24293-0, 13/07375-0)
BIRGIN, E. G.; MARTINEZ, J. M.. On polynomial predictions for river surface elevations. OPTIMIZATION AND ENGINEERING, v. N/A, p. 46-pg., . (22/05803-3, 13/07375-0, 23/08706-1)