Issue |
RAIRO-Oper. Res.
Volume 56, Number 3, May-June 2022
|
|
---|---|---|
Page(s) | 1353 - 1371 | |
DOI | https://doi.org/10.1051/ro/2022063 | |
Published online | 02 June 2022 |
Regularization algorithms for linear copositive problems
1
Institute of Mathematics, National Academy of Sciences of Belarus, Surganov str. 11, 220072 Minsk, Belarus
2
Department of Applied Mathematics and Computer Science, Belarusian State University, Nezavisimosti av. 4, 220030 Minsk, Belarus
3
Mathematical Department, University of Aveiro, Campus Universitário Santiago, 3810-193 Aveiro, Portugal
* Corresponding author: tatiana@ua.pt
Received:
15
December
2020
Accepted:
4
May
2022
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.
Mathematics Subject Classification: 90C25 / 90C46 / 90C30 / 90C34
Key words: Linear copositive programming / strong duality / normalized immobile index set / regularization / minimal cone / facial reduction / constraint qualifications
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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