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Élément Dublin Core | Valeur | Langue |
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dc.contributor.author | ABDERRAHIM, GUEMMAZ | - |
dc.date.accessioned | 2023-05-29T09:06:46Z | - |
dc.date.available | 2023-05-29T09:06:46Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://dspace.cu-barika.dz/jspui/handle/123456789/513 | - |
dc.description.abstract | Kernel functions serve the central goal of creating new search directions for the primal-dual interiorpoint algorithm to solve linear optimization problems. A significantly improved primal-dual interior-point algorithm for linear optimization is presented based on a novel kernel function. We show a primal-dual interior-point technique for linear optimization based on a class of kernel functions that are eligible. This research presents a new efficient kernel function-based primal-dual IPM algorithm for semidefinite programming problems based on the Nesterov-Todd (NT) direction. With a new and simple technique, we propose a new kernel function to obtain an optimal solution of the perturbed problem (SDP)m. | en_US |
dc.publisher | J. Math. Comput. Sci. | en_US |
dc.subject | linear semidefinite programming; central trajectory methods; | en_US |
dc.subject | primal-dual interior point methods | en_US |
dc.title | THEORETICAL AND NUMERICAL RESULT FOR LINEAR SEMIDEFINITE PROGRAMMING BASED ON A NEW KERNEL FUNCTION | en_US |
dc.type | Article | en_US |
Collection(s) : | Department of Maths - قسم الرياضيات |
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