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https://elib.bsu.by/handle/123456789/289549
Заглавие документа: | Regularization algorithms for linear copositive problems |
Авторы: | Kostyukova, Olga I. Tchemisova, Tatiana V. |
Тема: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
Дата публикации: | 2022 |
Издатель: | EDP Sciences |
Библиографическое описание источника: | RAIRO Oper Res 2022;56(3):1353-1371. |
Аннотация: | The paper is devoted to the regularization of linear Copositive Programming problems which consists of transforming a problem to an equivalent form, where the Slater condition is satisfied and therefore the strong duality holds. We describe regularization algorithms based on a concept of immobile indices and on the understanding of the important role that these indices play in the feasible sets' characterization. These algorithms are compared to some regularization procedures developed for a more general case of convex problems and based on a facial reduction approach. We show that the immobile-index-based approach combined with the specifics of copositive problems allows us to construct more explicit and detailed regularization algorithms for linear Copositive Programming problems than those already available. |
URI документа: | https://elib.bsu.by/handle/123456789/289549 |
DOI документа: | 10.1051/ro/2022063 |
Scopus идентификатор документа: | 85131693207 |
Финансовая поддержка: | The authors thank the anonymous referees for their very helpful comments and suggestions which aided us in improving the presentation of this paper. This work was partially supported by the state research program “Convergence” (Republic Belarus), Task 1.3.01, by Portuguese funds through CIDMA – Center for Research and Development in Mathematics and Applications, and FCT – Portuguese Foundation for Science and Technology, within the project UIDB/04106/2020. |
Лицензия: | info:eu-repo/semantics/openAccess |
Располагается в коллекциях: | Статьи факультета прикладной математики и информатики |
Полный текст документа:
Файл | Описание | Размер | Формат | |
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ro200572.pdf | 515,1 kB | Adobe PDF | Открыть |
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