[1] Abbaszadehpeivasti, H., de Klerk, E. and Zamani, M. On the rate of convergence of the
difference-of-convex algorithm (DCA), J. Optim. Theory. Appl., 202 (2024), 475–496.
[2] Achache, M. A new primal-dual path-following method for convex quadratic programming,
Comput. Appl. Math., 25(1) (2006), 97–110.
[3] Asadi, S. and Mansouri, H. A new full-Newton step O(n) infeasible interior-point algorithm
for P∗(κ)-horizontal linear complementarity problems, Comput. Sci. J. Mold., 64 (2014),
37–61.
[4] Asadi, S., Mansouri, H. and Darvay, Z. An infeasible full-NT step IPM for horizontal linear
complementarity problem over Cartesian product of symmetric cones, Optim., 66(2) (2016),
225–250.
[5] Bai, Y.Q., El Ghami, M. and Roos, C. A new efficient large-update primal-dual interior-point
method based on a finite barrier, SIAM J. Optim., 13(3) (2002), 766–782.
[6] Bouafia, M., Benterki, D. and Yassine, A. Complexity analysis of interior point methods for
linear programming based on a parameterized kernel function, RAIRO Oper. Res., 50(4-5)
(2016), 935–949.
[7] Boudjellal, N. and Benterki, D. A new full-Newton step feasible interior point method for
convex quadratic programming, Optimization, 73 (2024), 1571–1588.
[8] Boudjellal, N., Roumili, H. and Benterki, D. Complexity analysis of interior point methods
for convex quadratic programming based on a parameterized kernel function, Bol. Soc. Parana.
Mat., 40 (2022), 1–16.
[9] Chinchilla, R., Yang, G. and Hespanha, J.P. Newton and interior-point methods for (con-
strained) nonconvex–nonconcave minmax optimization with stability and instability guaran-
tees, Math. Control Signals Syst., 36 (2024), 381–421.
[10] Darvay, Z. A new algorithm for solving self-dual linear optimization problems, Studia Univ.
Babeș-Bolyai Informatica, 47 (2002), 15–26.
[11] Darvay, Z. New interior point algorithms in linear programming, Adv. Model. Optim., 5(1)
(2003), 51–92.
[12] Darvay, Z., Papp, I.M. and Takács, P.R. An infeasible full-Newton step algorithm for linear
optimization with one centering step in major iteration, Studia Univ. Babes-Bolyai Infor-
matica, 59 (1) (2014), 28–45.
[13] Darvay, Z., Papp, I. M. and Takács P. R. Complexity analysis of a full-Newton step interior-
point method for linear optimization, Period. Math. Hungar., 73 (2016), 27–42.
[14] Darvay, Z. and Takács, P. R. New method for determining search directions for interior-point
algorithms in linear optimization, Optim. Lett., 12 (2018), 1099–1116.
[15] Grimes, W. and Achache, M. A path-following interior-point algorithm for monotone LCP
based on a modified Newton search direction, RAIRO Oper. Res., 57(3) (2023), 1059–1073.
[16] Hock, W. Test examples for nonlinear programming codes. Springer Berlin, Heidelberg, 1981.
[17] Kheirfam, B. A new infeasible interior-point method based on Darvay’s technique for sym-
metric optimization, Ann. Oper. Res., 211 (2013), 209–224.
[18] Kheirfam, B. New complexity analysis of a full Nesterov–Todd step interior-point method
for semidefinite optimization, Asian-Eur. J. Math., 10(4) (2017), 1750070.
[19] Kheirfam, B. and Nasrollahi, A. An extension for identifying search directions for interior-
point methods in linear optimization, Asian-Eur. J. Math., 13 (2020), 2050014.
[20] LeThi, H.A., Le, H.M., Phan, D.N. and Tran, B. Novel DCA based algorithms for a special
class of nonconvex problems with application in machine learning, Appl. Math. Comput., 409
(2021), 125904.
[21] Li, X. and Zhang, M. Interior-point algorithm for linear optimization based on a new trigono-
metric kernel function, Oper. Res. Lett., 43(5) (2015), 471–475.
[22] Lukšan, L., Matonoha. C. and Vlček, J. Interior-point method for non-linear non-convex
optimization, Numerical linear algebra with applications, 11(5-6) (2004), 431–453.
[23] Mansouri, H. and Pirhaji, M. A polynomial interior-point algorithm for monotone linear
complementarity problems, J. Optim. Theory Appl., 157 (2013), 451–461.
[24] Maros, I. and Mészáros, C. A repository of convex quadratic programming problems, Opti-
mization methods and software, 11(1-4) (1999), 671–681.
[25] Phan, D.N. and Thi, H.A. Difference-of-convex algorithm with extrapolation for nonconvex,
nonsmooth optimization problems, Math. Oper. Res., 49(3) (2024), 1973–1985.
[26] Roumili, H. and Kebbiche, Z. A weighted target-following algorithm for linearly constrained
convex optimization, Int. J. Open Problems Compt. Math., 5(4) (2012), 25–33.
[27] Tahmasebzadeh, S., Navidi, H. and Malek, A. Novel interior point algorithms for solving
nonlinear convex optimization problems, Adv. Oper. Res., 2015 (2015).
[28] Vanderbei, R.J. and Shanno, D.F. An interior-point algorithm for nonconvex nonlinear
programming, Comput. Optim. Appl., 13 (1999) , 231–252.
[29] Wang, G.Q. A new polynomial interior-point algorithm for the monotone linear comple-
mentarity problem over symmetric cones with full NT-steps, Asia-Pac. J. Oper. Res., 29(2)
(2012), 1250015.
[30] Zaoui, B., Benterki, D. and Khelladi, S. New efficient descent direction of a primal-dual path-
following algorithm for linear programming, Stat. Optim. Inf. Comput., 12 (2024), 1098–1112.
[31] Zaoui, B., Benterki, D. and Khelladi, S. Efficient descent direction of a primal-dual interior
point algorithm for convex quadratic optimization, J. Inf. Optim. Sci., (2025). Available online.
[32] Zaoui, B., Benterki, D., Kraria, A. and Raouache, H. Interior-point algorithm for linear
programming based on a new descent direction, RAIRO Oper. Res., 57 (2023), 2473–2491.
[33] Zhang, M., Bai Y.Q. and Wang G.Q. A new primal-dual path-following interior-point algo-
rithm for linearly constrained convex optimization, Journal of Shanghai University (English
Edition), 12 (2008), 475–480.
[34] Zhang, M., Huang K., Li M. and Lv Y. A new full-Newton step interior-point method
for P∗(κ)-LCP based on a positive-asymptotic kernel function, J. Appl. Math. Comput., 64
(2020), 313–330.
