Open Access
Issue
RAIRO-Oper. Res.
Volume 57, Number 3, May-June 2023
Page(s) 1599 - 1616
DOI https://doi.org/10.1051/ro/2023094
Published online 30 June 2023
  • S. Asadi, H. Mansouri and M. Zangiabadi, A class of path-following interior-point methods for P*(κ)-horizontal linear complementarity problems. J. Oper. Res. Soc. China 3 (2015) 17–30. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Asadi, M. Zangiabadi and H. Mansouri, An infeasible interior-point algorithm with full-Newton steps for P*(κ)-horizontal linear complementarity problems based on a kernel function. J. Appl. Math. Comput. 50 (2016) 15–37. [CrossRef] [MathSciNet] [Google Scholar]
  • Y.Q. Bai, M. El Ghami and C. Roos, A comparative study of kernel functions for primal-dual interior point algorithms in linear optimization. SIAM J. Optim. 15 (2005) 101–128. [Google Scholar]
  • M. Bouafia, D. Benterki and A. Yassine, An efficient primal-dual interior point method for linear programming problems based on a new kernel function with a trigonometric barrier term. J. Optim. Theory Appl. 170 (2016) 528–545. [CrossRef] [MathSciNet] [Google Scholar]
  • X.Z. Cai, L. Li, M. El Ghami, T. Steihaug and G.Q. Wang, A new parametric kernel function yielding the best known iteration bounds of interior-point methods for the Cartesian P*(κ)-LCP over symmetric cones. Pacific J. Optim. 13 (2017) 547–570. [MathSciNet] [Google Scholar]
  • M. El Ghami and G.Q. Wang, Interior-point methods for P*(κ)-linear complementarity problem based on generalized trigonometric barrier function. Int. J. Appl. Math. 30 (2017) 11–33. [CrossRef] [MathSciNet] [Google Scholar]
  • M. El Ghami, I. Ivanov, J.B.M. Melissen, C. Roos and T. Steihaug, A polynomial-time algorithm for linear optimization based on a new class of kernel functions. J. Comput. Appl. Math. 224 (2009) 500–513. [Google Scholar]
  • M. El Ghami, Z.A. Guennoun, S. Bouali and T. Steihaug, Interior point methods for linear optimization based on a kernel function with a trigonometric barrier term. J. Comput. Appl. Math. 236 (2012) 3613–3623. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Fathi-Hafshejani and A.F. Jahromi, An interior pointmethod for P*(κ)-horizontal linear complementarity problem based on a new proximity function. J. Appl. Math. Comput. 62 (2020) 281–300. [CrossRef] [MathSciNet] [Google Scholar]
  • N. Hazzam and Z. Kebbiche, A primal-dual interior point method for P*(κ)-HLCP based on a class of parametric kernel functions. Numer. Algebra Control Optimiz. 11 (2021) 513–531. [CrossRef] [Google Scholar]
  • B. Kheirfam, A new search direction for full-newton stepinterior-point method in P*(κ)-HLCP. J. Numer. Funct. Anal. Optim. 40 (2019) 1169–1181. [CrossRef] [Google Scholar]
  • M. Kojima, N. Megiddo, T. Noma and A. Yoshise, A unified approach to interior point algorithms for linear complementarity problems, in Lecture Notes in Computer Science, Springer-Verlag, Berlin (1991). [CrossRef] [Google Scholar]
  • Y.H. Lee, Y.Y. Cho and G.M. Cho, Kernel function based interior-point methodsfor horizontal linear complementarity problems. J. Inequal. Appl. 2013 (2013) 215–229. [CrossRef] [Google Scholar]
  • G. Lesaja and C. Roos, Unified analysis of kernel-based interior-point methods for P*(κ)-LCP. SIAM J. Optim. 20 (2010) 3014–3039. [CrossRef] [MathSciNet] [Google Scholar]
  • L. Li, J.Y. Tao, M. El Ghami, X.Z. Cai and G.Q. Wang, A new parametric kernel function with a trigonometric barrier term for P*(κ)-linear complementarity problems. Pacific J. Optim. 13 (2017) 255–278. [MathSciNet] [Google Scholar]
  • Cs. Meszaros, Steplengths in interior-point algorithms of quadratic programming. Oper. Res. Lett. 213 (1999) 39–45. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Peng, C. Roos and T. Terlaky, Self-Regularity: A New Paradigm for Primal-Dual interior point Algorithms. Princeton University Press, Princeton, NJ (2002). [Google Scholar]
  • M.R. Peyghami and S.F. Hafshejani, Complexity analysis of an interior point algorithm for linear optimization based on a new proximity function. Numer. Algo. 67 (2014) 33–48. [CrossRef] [Google Scholar]
  • M.R. Peyghami, S.F. Hafshejani and L. Shirvani, Complexity of interior point methods for linear optimization based on a new trigonometric kernel function. J. Comput. Appl. Math. 255 (2014) 74–85. [CrossRef] [MathSciNet] [Google Scholar]
  • C. Roos, T. Terlaky and J.Ph Vial, Theory and algorithms for linear optimization, in An interior point Approach. John Wiley & Sons, Chichester, UK (1997). [Google Scholar]
  • G.Q. Wang and Y.Q. Bai, Polynomial interior-point algorithm for P*(κ)-horizontal linear complementarity problem. J. Comput. Appl. Math. 233 (2009) 248–263. [Google Scholar]
  • G.Q. Wang and G. Lesaja, Full Nesterov-Todd step feasible interior-point methodfor the Cartesian P*(κ)-SCLCP. Optim. Methods. Soft. 28 (2013) 600–618. [CrossRef] [Google Scholar]
  • G.Q. Wang, C.J. Yu and K.L. Teo, A full-Newton step feasible interior-point algorithm for P*(κ)-linear complementarity problem. J. Global Optim. 59 (2014) 81–99. [CrossRef] [MathSciNet] [Google Scholar]
  • G.Q. Wang, X.J. Fan, D.T. Zhu and D.Z. Wang, New complexity analysis of a full Newton step feasible interior-point algorithm for P*(κ)-LCP. Optim. Lett. 9 (2015) 1105–1119. [CrossRef] [MathSciNet] [Google Scholar]

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