Publications

Hadjisavvas, N. & Lara, F. (2026). Characterizations of Strongly Quasiconvex Functions. Journal of Global Optimization, 94(4), 997–1003. https://doi.org/10.1007/s10898-026-01611-y

Hadjisavvas, N., Lara, F., Marcavillaca, R., & Vuong, P. (2026). Heavy Ball and Nesterov Accelerations with Hessian-Driven Damping for Nonconvex Optimization. Applied Mathematics and Optimization, 93(3). https://doi.org/10.1007/s00245-026-10406-2

Lara, F. & Ramos, A. (2026). On Optimality Conditions for Mathematical Programming Problems Based on Strong Subdifferentials. Set-Valued and Variational Analysis, 34(2). https://doi.org/10.1007/s11228-026-00802-9

Lara, F. & Thang, T. V. (2026). Proximal point type algorithms for solving multiobjective optimization problems beyond convexity. Optimization, 75(3), 589–614. https://doi.org/10.1080/02331934.2026.2628001

Lara, F., Marcavillaca, R., & Thang, T. (2026). A subgradient projection method for quasiconvex multiobjetive optimization. Optimization, 75(4), 705–727. https://doi.org/10.1080/02331934.2024.2436577

Lara, F., Pandey, R., & Singh, V. (2026). Optimality conditions and duality for multiobjective fractional bilevel optimization problems. Computational and Applied Mathematics, 45(6). https://doi.org/10.1007/s40314-026-03644-1

de Brito, J. M. M., Lara, F., & Van Thang, T. (2026). Splitting proximal point algorithms for the sum of prox-convex functions. Computational and Applied Mathematics, 45(7). https://doi.org/10.1007/s40314-026-03677-6

Grad, S., Lara, F., & Marcavillaca, R. T. (2025). Strongly Quasiconvex Functions: What We Know (So Far). Journal of Optimization Theory and Applications, 205(2). https://doi.org/10.1007/s10957-025-02641-4

Lara, F. & Vega, C. (2025). Delayed feedback in online non-convex optimization: A non-stationary approach with applications. Numerical Algorithms. https://doi.org/10.1007/s11075-025-02276-6

Lara, F. & Yen, L. H. (2025). On the Minimization of the Sum of Nonconvex Functions with Applications to Mathematical Programming. Journal of Global Optimization. https://doi.org/10.1007/s10898-025-01520-6

Lara, F., Marcavillaca, R. T., & Vuong, P. T. (2025). Characterizations, Dynamical Systems and Gradient Methods for Strongly Quasiconvex Functions. Journal of Optimization Theory and Applications, 206(3). https://doi.org/10.1007/s10957-025-02728-y

Lara, F., Van Tuyen, N., & Van Nghi, T. (2025). Weak sharp minima at infinity and solution stability in mathematical programming via asymptotic analysis. Journal of Global Optimization, 92(4), 933–950. https://doi.org/10.1007/s10898-025-01516-2

Phuoc Hai, L., Lara, F., & Mordukhovich, B. S. (2025). Regular Subgradients of Marginal Functions with Applications to Calculus and Bilevel Programming. Journal of Optimization Theory and Applications, 205(2). https://doi.org/10.1007/s10957-025-02635-2

Choque, J., Lara, F., & Marcavillaca, R. T. (2024). A subgradient projection method for quasiconvex minimization. Positivity, 28(5). https://doi.org/10.1007/s11117-024-01082-z

Grad, S., Lara, F., & Marcavillaca, R. (2024). Proximal point type algorithms with relaxed and inertial effects beyond convexity. Optimization, 73(11), 3393–3410. https://doi.org/10.1080/02331934.2024.2329779

Grad, S., Lara, F., & Tintaya Marcavillaca, R. (2024). Relaxed-Inertial Proximal Point Algorithms for Nonconvex Equilibrium Problems with Applications. Journal of Optimization Theory and Applications, 203(3), 2233–2262. https://doi.org/10.1007/s10957-023-02375-1

Iusem, A., Lara, F., Marcavillaca, R. T., & Yen, L. H. (2024). A Two-Step Proximal Point Algorithm for Nonconvex Equilibrium Problems with Applications to Fractional Programming. Journal of Global Optimization, 90(3), 755–779. https://doi.org/10.1007/s10898-024-01419-8

Lara, F. & Marcavillaca, R. (2024). Bregman proximal point type algorithms for quasiconvex minimization. Optimization, 73(3), 497–515. https://doi.org/10.1080/02331934.2022.2112580

Lara, F., Marcavillaca, R., & Yen, L. (2024). An extragradient projection method for strongly quasiconvex equilibrium problems with applications. Computational and Applied Mathematics, 43(3). https://doi.org/10.1007/s40314-024-02626-5

Grad, S., Lara, F., & Marcavillaca, R. (2023). Relaxed-inertial proximal point type algorithms for quasiconvex minimization. Journal of Global Optimization, 85(3), 615–635. https://doi.org/10.1007/s10898-022-01226-z

Kabgani, A. & Lara, F. (2023). Semistrictly and neatly quasiconvex programming using lower global subdifferentials. Journal of Global Optimization, 86(4), 845–865. https://doi.org/10.1007/s10898-023-01278-9

Grad, S. & Lara, F. (2022). An extension of the proximal point algorithm beyond convexity. Journal of Global Optimization, 82(2), 313–329. https://doi.org/10.1007/s10898-021-01081-4

Iusem, A. & Lara, F. (2022). Proximal Point Algorithms for Quasiconvex Pseudomonotone Equilibrium Problems. Journal of Optimization Theory and Applications, 193(1-3), 443–461. https://doi.org/10.1007/s10957-021-01951-7

Kabgani, A. & Lara, F. (2022). Strong subdifferentials: theory and applications in nonconvex optimization. Journal of Global Optimization, 84(2), 349–368. https://doi.org/10.1007/s10898-022-01149-9

Lara, F. (2022). Characterizations of nonconvex optimization problems via variational inequalities. Optimization, 71(9), 2471–2490. https://doi.org/10.1080/02331934.2020.1857758

Lara, F. (2022). On Nonconvex Pseudomonotone Equilibrium Problems with Applications. Set-Valued and Variational Analysis, 30(2), 355–372. https://doi.org/10.1007/s11228-021-00586-0

Lara, F. (2022). On Strongly Quasiconvex Functions: Existence Results and Proximal Point Algorithms. Journal of Optimization Theory and Applications, 192(3), 891–911. https://doi.org/10.1007/s10957-021-01996-8

Grad, S. & Lara, F. (2021). Solving Mixed Variational Inequalities Beyond Convexity. Journal of Optimization Theory and Applications, 190(2), 565–580. https://doi.org/10.1007/s10957-021-01860-9

Lara, F. & Kabgani, A. (2021). On global subdifferentials with applications in nonsmooth optimization. Journal of Global Optimization, 81(4), 881–900. https://doi.org/10.1007/s10898-020-00981-1

Bueno, L., Haeser, G., Lara, F., & Rojas, F. (2020). An Augmented Lagrangian method for quasi-equilibrium problems. Computational Optimization and Applications, 76(3), 737–766. https://doi.org/10.1007/s10589-020-00180-4

Hadjisavvas, N., Lara, F., & Luc, D. T. (2020). A general asymptotic function with applications in nonconvex optimization. Journal of Global Optimization, 78(1), 49–68. https://doi.org/10.1007/s10898-020-00891-2

Iusem, A. & Lara, F. (2020). A Note on “Existence Results for Noncoercive Mixed Variational Inequalities in Finite Dimensional Spaces”. Journal of Optimization Theory and Applications, 187(2), 607–608. https://doi.org/10.1007/s10957-020-01722-w

Iusem, A. & Lara, F. (2020). Quasiconvex optimization problems and asymptotic analysis in Banach spaces. Optimization, 69(11), 2453–2470. https://doi.org/10.1080/02331934.2019.1612893

Lara, F. (2020). On the existence of a saddle value for nonconvex and noncoercive bifunctions. Minimax Theory and its Applications, 5(1), 65–76.

Lara, F. (2020). Optimality Conditions for Nonconvex Nonsmooth Optimization via Global Derivatives. Journal of Optimization Theory and Applications, 185(1), 134–150. https://doi.org/10.1007/s10957-019-01613-9

Hadjisavvas, N., Lara, F., & Martínez-Legaz, J. E. (2019). A Quasiconvex Asymptotic Function with Applications in Optimization. Journal of Optimization Theory and Applications, 180(1), 170–186. https://doi.org/10.1007/s10957-018-1317-2

Iusem, A. & Lara, F. (2019). Existence Results for Noncoercive Mixed Variational Inequalities in Finite Dimensional Spaces. Journal of Optimization Theory and Applications, 183(1), 122–138. https://doi.org/10.1007/s10957-019-01548-1

Iusem, A. & Lara, F. (2019). Optimality Conditions for Vector Equilibrium Problems with Applications. Journal of Optimization Theory and Applications, 180(1), 187–206. https://doi.org/10.1007/s10957-018-1321-6

Iusem, A. & Lara, F. (2019). The q-asymptotic function in c-convex analysis. Optimization, 68(7), 1429–1445. https://doi.org/10.1080/02331934.2018.1456540

Lara, F. (2019). Quadratic fractional programming under asymptotic analysis. Journal of Convex Analysis, 26(1), 15–32.

Lara, F., López, R., & Svaiter, B. F. (2019). A Further Study on Asymptotic Functions via Variational Analysis. Journal of Optimization Theory and Applications, 182(1), 366–382. https://doi.org/10.1007/s10957-019-01507-w

Iusem, A. N. & Lara, F. (2018). Second order asymptotic functions and applications to quadratic programming. Journal of Convex Analysis, 25(1), 271–291.

Lara, F. (2018). A note on “Reguralizers for structured sparsity”. Advances in Computational Mathematics, 44(4), 1321–1323. https://doi.org/10.1007/s10444-017-9583-3

Lara, F. & López, R. (2017). Formulas for Asymptotic Functions via Conjugates, Directional Derivatives and Subdifferentials. Journal of Optimization Theory and Applications, 173(3), 793–811. https://doi.org/10.1007/s10957-017-1101-8

Lara, F. (2017). Generalized asymptotic functions in nonconvex multiobjective optimization problems. Optimization, 66(8), 1259–1272. https://doi.org/10.1080/02331934.2016.1235162

Lara, F. (2017). Second-order asymptotic analysis for noncoercive convex optimization. Mathematical Methods of Operations Research, 86(3), 469–483. https://doi.org/10.1007/s00186-017-0605-1

Flores-Bazán, F., Hadjisavvas, N., Lara, F., & Montenegro, I. (2016). First- and Second-Order Asymptotic Analysis with Applications in Quasiconvex Optimization. Journal of Optimization Theory and Applications, 170(2), 372–393. https://doi.org/10.1007/s10957-016-0938-6

Flores-Bazán, F., Hadjisavvas, N., & Lara, F. (2015). Second order asymptotic analysis: Basic theory. Journal of Convex Analysis, 22(4), 1173–1196.

Projects

1

Dynamical systems associated to nonconvex optimization problems.

2

A further study on quasiconvex functions with applications in continuous optimization and variational inequalities.

3

Interactions between Optimization, Dynamic Systems, and Geometry.

4

Optimality conditions and proximal methods for generalized convex optimization problems.

5

Further developments on quasiconvex functions with applications in continuous optimization and equilibrium problems.