Published in Universidade Federal de Goiás (UFG), 2019
Mestrado em Matemática - Universidade Federal de Goiás.
Recommended citation: SOUZA, D. R. Método do gradiente conjugado Dai-Yuan modificado para otimização irrestrita. 2019. 71 f. Dissertação (Mestrado em Matemática) - Universidade Federal de Goiás, Goiânia, 2019.
Paper
Published in Journal of Optimization Theory and Applications, 2022
Recommended citation: L. F. Prudente and D. R. Souza. (2022). "A quasi-Newton method with Wolfe line searches for multiobjective optimization." Journal of Optimization Theory and Applications 194, pp. 1107-1140.
Paper | Code | DOI
Published in Computational Optimization and Applications, 2024
Global convergence analysis of a BFGS-type algorithm for nonconvex multiobjective optimization.
Recommended citation: L. F. Prudente and D. R. Souza. (2024). "Global convergence of a BFGS-type algorithm for nonconvex multiobjective optimization problems." Computational Optimization and Applications 88(3), pp. 719-757.
Paper | Code | DOI
Published in ESAIM: Control, Optimisation and Calculus of Variations, 2024
Reconstruction of Voronoi diagrams in inverse potential problems.
Recommended citation: E. G. Birgin, A. Laurain, and D. R. Souza. (2024). "Reconstruction of Voronoi diagrams in inverse potential problems." ESAIM: Control, Optimisation and Calculus of Variations 30, article number 85.
Paper | Code | DOI
Published in Inverse Problems, 2024
Reconstruction of Voronoi diagrams in inverse conductivity problems.
Recommended citation: E. G. Birgin, A. Laurain, and D. R. Souza. (2025). "Reconstruction of Voronoi diagrams: the case of inverse conductivity problems." Inverse Problems 41, 055007.
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Published in arXiv, 2026
A partially derivative-free proximal method for composite multiobjective optimization in the Holder setting.
Recommended citation: V. S. Amaral, P. B. Assuncao, and D. R. Souza. (2026). "A Partially Derivative-Free Proximal Method for Composite Multiobjective Optimization in the Holder Setting." arXiv:2508.20071 [math.OC].
Paper | Code | DOI
Published:
A BFGS method with Wolfe line search for multiobjective optimization, with global and local convergence results.
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A BFGS method with Wolfe line searches for unconstrained multiobjective optimization, with global and local convergence results.
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We will address the fundamentals and recent advances in stochastic optimization methods, essential techniques for large-scale problems.
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An overview of multiobjective optimization strategies, with emphasis on direct vector methods.