Unified representation of the classical ellipsoid method
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
A parametric version of the ellipsoid method with space scaling by a scalar parameter λ > 0 is considered. For certain values of the parameter λ, it is reduced to the well-known versions of the ellipsoid method, namely, the Shor, Khachiyan, Nemirovsky, and Yudin ones. The properties of two algorithmic implementations of the parameterized ellipsoid method are proved. The first algorithm is based on updating the asymmetric matrix B, and the second one updates the symmetric matrix H = BBT. The applications of the algorithms for solving convex programming problems and finding the saddle point of a convex-concave function are described.
Details
Original language | English |
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Pages (from-to) | 784-793 |
Number of pages | 10 |
Journal | Cybernetics and Systems Analysis |
Volume | 59 |
Issue number | 5 |
Publication status | Published - Sept 2023 |
Peer-reviewed | Yes |
External IDs
Scopus | 85173251021 |
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Mendeley | 610f84cf-6ed1-3e66-80d0-181eabe3efea |
Keywords
Research priority areas of TU Dresden
DFG Classification of Subject Areas according to Review Boards
Subject groups, research areas, subject areas according to Destatis
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- convex programming, ellipsoid method, saddle point, space dilation