域驱动求解器（DDS）2.0版：一个基于MATLAB的域驱动形式的凸优化软件包
Domain-Driven Solver (DDS) Version 2.0: a MATLAB-based Software Package for Convex Optimization Problems in Domain-Driven Form
摘要：
Domain-Driven Solver（DDS）是一个基于MATLAB的软件包，用于以Domain-Driven形式解决凸优化问题[Karimi and Tunçel，arXiv：1804.06925]。DDS的当前版本接受以下函数/集合约束的所有组合：（1）对称圆锥（LP，SOCP和SDP）;（2）SOCP可表示的二次约束;（3）定义为单变量凸函数的epigraphs的任意二维凸集集合的直和（包括作为特例的几何规划和熵规划）;（4）广义幂锥;（5）矩阵范数上图（包括作为线性子空间上的核范数的特殊情况的最小化）;（6）向量相对熵;（7）量子熵和量子相对熵的epigraphs;以及（8）涉及双曲多项式的约束。DDS是[Karimi and Tunçel，arXiv：1804.06925]中设计和分析的不可行启动原始对偶法的实际实现。这份手稿包含了用户指南，以及算法实现所需的理论结果。为了帮助用户，我们提供了许多示例。我们还讨论了一些实现细节和技术，我们用来提高效率和进一步扩展的软件，以涵盖新兴类的凸优化问题。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
