Implementation and evaluation of SDPA 6.0 (Semidefinite Programming Algorithm 6.0)
Implementation and evaluation of SDPA 6.0 (Semidefinite Programming Algorithm 6.0)
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DOI：
10.1080/1055678031000118482
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发表时间：
2003-08
影响因子：
2.2
通讯作者：
M. Yamashita;K. Fujisawa;M. Kojima
中科院分区：
文献类型：
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作者：
M. Yamashita;K. Fujisawa;M. Kojima
半定规划（SDP）是最具吸引力的优化模型之一。它在控制理论、组合优化与鲁棒优化以及量子化学等多个领域都有诸多应用。半定规划算法（SDPA）是一个基于原始 - 对偶内点法以及HRVW/KSH/M搜索方向来求解一般半定规划问题的软件包。它借助用于稠密矩阵计算的数值线性代数库LAPACK，用C++编写而成。本文的目的是通过数值实验以及与其他一些用于一般半定规划的主要软件包进行比较，对最新版的SDPA及其在大规模问题上的高性能进行简要描述。
SDP (SemiDefinite Programming) is one of the most attractive optimization models. It has many applications from various fields such as control theory, combinatorial and robust optimization, and quantum chemistry. The SDPA (SemiDefinite Programming Algorithm) is a software package for solving general SDPs based on primal-dual interior-point methods with the HRVW/KSH/M search direction. It is written in C++ with the help of LAPACK for numerical linear algebra for dense matrix computation. The purpose of this paper is to present a brief description of the latest version of the SDPA and its high performance for large scale problems through numerical experiments and comparisons with some other major software packages for general SDPs.