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Complexity analysis of primal-dual interior-point methods for convex quadratic programming based on a new twice parameterized kernel function | ||
| Journal of Mathematical Modeling | ||
| مقاله 5، دوره 12، شماره 2، مهر 2024، صفحه 247-265 اصل مقاله (205.87 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2024.25394.2257 | ||
| نویسندگان | ||
| Youssra Bouhenache* 1؛ Wided Chikouche1؛ Imene Touil1؛ Sajad Fathi-Hafshejani2 | ||
| 1Laboratory of Pure and Applied Mathematics, Faculty of Exact Sciences and Informatics, University of Jijel, 18000 Jijel, Algeria | ||
| 2Shiraz University of Technology, Fars 71557-13876, Shiraz, Iran | ||
| چکیده | ||
| In this paper, we present primal-dual interior-point methods (IPMs) for convex quadratic programming (CQP) based on a new twice parameterized kernel function (KF) with a hyperbolic barrier term. To our knowledge, this is the first KF with a twice parameterized hyperbolic barrier term. By using some conditions and simple analysis, we derive the currently best-known iteration bounds for large- and small-update methods, namely, $\textbf{O}\big(\sqrt{n}\log n\log\frac{n}{\epsilon}\big)$ and $\textbf{O}\big(\sqrt{n}\log\frac{n}{\epsilon}\big)$, respectively, with special choices of the parameters. Finally, some numerical results regarding the practical performance of the new proposed KF are reported. | ||
| کلیدواژه‌ها | ||
| Convex quadratic programming؛ Kernel function؛ Interior-point methods؛ Large- and small-update methods | ||
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آمار تعداد مشاهده مقاله: 199 تعداد دریافت فایل اصل مقاله: 214 |
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