Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/36132
Title: | Regularization algorithms for linear copositive problems |
Author: | Kostyukova, Olga I. Tchemisova, Tatiana V. |
Keywords: | Linear copositive programming Strong duality Normalized immobile index set Regularization Minimal cone Facial reduction Constraint qualifications |
Issue Date: | 2022 |
Publisher: | DP Sciences |
Abstract: | 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 con struct more explicit and detailed regularization algorithms for linear Copositive Programming problems than those already available. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/36132 |
DOI: | 10.1051/ro/2022063 |
ISSN: | 0399-0559 |
Appears in Collections: | CIDMA - Artigos OGTCG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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EF08E5F4456142709B1D881F280297CB.pdf | 498.84 kB | Adobe PDF | View/Open |
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