Domain-Driven Solver (DDS) Version 2.0: 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 optimization problems in Domain-Driven form [Karimi and Tunçel, arXiv:1804.06925]. 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 power cone; (5) epigraphs of matrix norms (including as a special case minimization of nuclear norm over a linear subspace); (6) vector relative entropy; (7) epigraphs of quantum entropy and quantum relative entropy; and (8) constraints involving hyperbolic polynomials. DDS is a practical implementation of the infeasible-start primal-dual algorithm designed and analyzed in [Karimi and Tunçel, arXiv:1804.06925]. This manuscript contains the users’ guide, as well as theoretical results needed for the implementation of the algorithms. To help the users, we included many examples. We also discussed some implementation details and techniques we used to improve the efficiency and further expansion of the software to cover the emerging classes of convex optimization problems.
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References in zbMATH (referenced in 2 articles )
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- Dávid Papp, Sercan Yıldız: alfonso: Matlab package for nonsymmetric conic optimization (2021) arXiv
- Lourenço, Bruno F.; Muramatsu, Masakazu; Tsuchiya, Takashi: Solving SDP completely with an interior point oracle (2021)