Implementation and evaluation of SDPA 6.0 (Semidefinite Programming Algorithm 6.0)

Makoto Yamashita, Katsuki Fujisawa, Masakazu Kojima

Research output: Contribution to journalArticlepeer-review

126 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)491-505
Number of pages15
JournalOptimization Methods and Software
Issue number4 II
Publication statusPublished - Aug 2003
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Optimization
  • Applied Mathematics


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