Open Access
Issue |
RAIRO-Oper. Res.
Volume 56, Number 2, March-April 2022
|
|
---|---|---|
Page(s) | 731 - 750 | |
DOI | https://doi.org/10.1051/ro/2022032 | |
Published online | 14 April 2022 |
- Y.Q. Bai and C. Roos, A primal-dual interior point method based on a new kernel function with linear growth rate. In Proceedings of the 9th Australian Optimization Day, Perth, Australia (2002). [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 and A. Yassine, An efficient twice parameterized trigonometric kernel function for linear optimization. Optim. Eng. 21 (2020) 651–672. [CrossRef] [MathSciNet] [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]
- 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, H. Mansourib, M.R. Peyghamic and S. Chene, Primal–dual interior-pointmethod for linear optimization based on a kernel function with trigonometric growth term. Optimization 67 (2018) 1605–1630. [CrossRef] [MathSciNet] [Google Scholar]
- N.K. Karmarkar, A new polynomial-time algorithm for linear programming. In Vol. 4 of Proceedings of the 16th Annual ACM Symposium on Theory of Computing (1984) 373–395. [Google Scholar]
- X. Li and M. Zhang, Interior-point algorithm for linear optimization based on a new trigonometric kernel function. Oper. Res. Lett. 43 (2015) 471–475. [CrossRef] [MathSciNet] [Google Scholar]
- N. Megiddo, Pathways to the optimal set in linear programming. In Progress in Mathematical Programming: Interior Point and Related Methods, edited by N. Megiddo, Springer-Verlag, New York (1989) 131–158. [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 JPh Vial, Theory and algorithms for linear optimization, In An interior point Approach, John Wiley & Sons, Chichester, UK (1997). [Google Scholar]
- G. Sonnevend, An “analytic center” for polyhedrons and new classes of global algorithms for linear (smooth, convex) programming. In Vol. 84 of System Modelling and Optimization: Proceedings of the 12th IFIP-Conference, Budapest, Hungary, 1985, in: Lecture Notes in Control and Inform. Sci., edited by A. Prekopa, J. Szelezsan, B. Strazicky. Springer-Verlag, Berlin (1986) 866–876. [CrossRef] [Google Scholar]
- Y. Ye, Interior point algorithms. Theory and Analysis, John-Wiley Sons, Chichester, UK (1997). [CrossRef] [Google Scholar]
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