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Domain-Driven Solver (DDS) Version 2.1: a MATLAB-based software package for convex optimization problems in domain-driven form
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DOI：10.1007/s12532-023-00248-2.png)
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摘要
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Domain-Driven Solver (DDS) is a MATLAB-based software package for convex optimization. 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 relative entropy; (7) epigraphs of quantum entropy and quantum relative entropy; and (8) constraints involving hyperbolic polynomials. The infeasible-start primal-dual algorithms 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.
Keyword:
Convex optimization
Software package
Self-concordant functions
Interior-point methods
Primal-dual algorithms
Duality theory
期刊
IF:
3.6
论文数:
202
被引数:
1.9K
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