Domain-Driven Solver (DDS) Version 2.1: a MATLAB-based software package for convex optimization problems in domain-driven form

  • Domain-Driven Solver (DDS) is a MATLAB-based software package for convex opti- mization. The current version of DDS accepts every combination of the following function/set constraints: (1) symmetric cones (LP, SOCP, and SDP); (2) quadratic constraints that are SOCP representable; (3) direct sums of an arbitrary collection of 2-dimensional convex sets defined as the epigraphs of univariate convex functions (including as special cases geometric programming and entropy programming); (4) generalized Koecher (power) cone; (5) epigraphs of matrix norms (including as a special case minimization of nuclear norm over a linear subspace); (6) vector rela- tive entropy; (7) epigraphs of quantum entropy and quantum relative entropy; and (8) constraints involving hyperbolic polynomials. The infeasible-start primal-dual algo- rithms used for DDS rely heavily on duality theory and properties of Legendre-Fenchel conjugate functions, and are designed to rigorously determine the status of a given problem. We discuss some important implementation details and techniques we used to improve the robustness and efficiency of the software. The appendix contains many examples.

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Metadaten
Author:Mehdi Karimi, Levent Tunçel
DOI:https://doi.org/10.1007/s12532-023-00248-2
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2023
Volume:16
Issue:1
Page Number:56
First Page:37
Last Page:92
Mathematical Programming Computation :MPC 2024 - Issue 1
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