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Title: A new parameterized logarithmic kernel function for linear optimization with a double barrier term yielding the best known iteration bound (English)
Author: Ayache, Benhadid
Author: Khaled, Saoudi
Language: English
Journal: Communications in Mathematics
ISSN: 1804-1388 (print)
ISSN: 2336-1298 (online)
Volume: 28
Issue: 1
Year: 2020
Pages: 27-41
Summary lang: English
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Category: math
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Summary: In this paper, we propose a large-update primal-dual interior point algorithm for linear optimization. The method is based on a new class of kernel functions which differs from the existing kernel functions in which it has a double barrier term. The investigation according to it yields the best known iteration bound $O(\sqrt {n} \log (n) \log (\frac {n}{\varepsilon }) )$ for large-update algorithm with the special choice of its parameter $m$ and thus improves the iteration bound obtained in Bai et al.~\cite {El Ghami2004} for large-update algorithm. (English)
Keyword: Linear optimization
Keyword: Kernel function
Keyword: Interior point methods
Keyword: Complexity bound
MSC: 90C05
MSC: 90C31
MSC: 90C51
idZBL: Zbl 1465.90041
idMR: MR4124288
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Date available: 2020-07-22T11:49:23Z
Last updated: 2021-11-01
Stable URL: http://hdl.handle.net/10338.dmlcz/148259
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Reference: [1] Bai, Y.Q., Roos, C.: A primal-dual interior point method based on a new kernel function with linear growth rate.Proceedings of the 9th Australian Optimization Day, Perth, Australia, 2002, 14p,
Reference: [2] Bai, Y.Q., Ghami, M. El, Roos, C.: A comparative study of kernel functions for primal-dual interior point algorithms in linear optimization.SIAM J. Optim., 15, 2004, 101-128, MR 2112978, 10.1137/S1052623403423114
Reference: [3] Bouaafia, M., Benterki, D., Adnan, Y.: Complexity analysis of interior point methods for linear programming based on a parameterized kernel.RAIRO-Oper. Res., 50, 2016, 935-949, MR 3570540, 10.1051/ro/2015056
Reference: [4] Bouaafia, M., Benterki, D., Adnan, Y.: An efficient parameterized logarithmic kernel function for linear optimization.Optim. Lett., 12, 2018, 1079-1097, MR 3819677, 10.1007/s11590-017-1170-5
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Reference: [11] Peng, J., Roos, C., Terlaky, T.: Self-Regularity: A New Paradigm for Primal-Dual Interior Point Algorithms.2002, Princeton University Press, Princeton, MR 1938497
Reference: [12] Roos, C., Terlaky, T., Vial, J.P.: Theory and Algorithms for Linear Optimization, An Interior Point Approach.1997, Wiley, Chichester, MR 1450094
Reference: [13] Sonnevend, G.: An ``analytic center'' for polyhedrons and new classes of global algorithms for linear (smooth, convex) programming.System Modelling and Optimization: Proceedings of the 12th IFIP-Conference, Budapest, Hungary, Lecture Notes in Control and Information Science, 84, 1986, 866-876, Springer, Berlin, MR 0903521
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