论文标题
HDSDP：半决赛编程软件
HDSDP: Software for Semidefinite Programming
论文作者
论文摘要
HDSDP是一个解决半决赛编程问题的数值软件。 HDSDP的主要框架类似于双缩放的内部点求解器DSDP [BY2008]，并且已经实现了基于简化均匀的自偶嵌入的双重方法，包括双重方法。嵌入技术增强了双重方法的稳定性，几种新的启发式方法和计算技术旨在加速其收敛性。 HDSDP旨在展示双级缩放算法如何从自偶嵌入中受益，并且与DSDP5.8并行开发。几个经典基准数据集的数值实验表现出其稳健性和效率，尤其是其在具有低级结构和稀疏性的SDP实例上的优势。 HDSDP根据MIT许可开源，可在https://github.com/copt-public/hdsdp上获得。
HDSDP is a numerical software solving the semidefinite programming problems. The main framework of HDSDP resembles the dual-scaling interior point solver DSDP [BY2008] and several new features, including a dual method based on the simplified homogeneous self-dual embedding, have been implemented. The embedding technique enhances stability of the dual method and several new heuristics and computational techniques are designed to accelerate its convergence. HDSDP aims to show how dual-scaling algorithm benefits from the self-dual embedding and it is developed in parallel to DSDP5.8. Numerical experiments over several classical benchmark datasets exhibit its robustness and efficiency, and particularly its advantages on SDP instances featuring low-rank structure and sparsity. HDSDP is open-sourced under MIT license and available at https://github.com/COPT-Public/HDSDP.
