Abstract
This paper describes CSDP, a library of routines that implements a predictor corrector variant of the semidefinite programming algorithm of Helmberg, Rendl, Vanderbei, and Wolkowicz. The main advantages of this code are that it can be used as a stand alone solver or as a callable subroutine, that it is written in C for efficiency, that it makes effective use of sparsity in the constraint matrices, and that it includes support for linear inequality constraints in addition to linear equality constraints. We discuss the algorithm used, its computational complexity, and storage requirements. Finally, we present benchmark results for a collection of test problems.
Keywords
SubroutineSemidefinite programmingBenchmark (surveying)SolverComputer scienceLinear programmingCode (set theory)Constraint (computer-aided design)Constraint programmingMathematical optimizationAlgorithmProgramming languageMathematicsStochastic programming
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Publication Info
- Year
- 1999
- Type
- article
- Volume
- 11
- Issue
- 1-4
- Pages
- 613-623
- Citations
- 500
- Access
- Closed
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Cite This
Brian Borchers
(1999).
CSDP, A C library for semidefinite programming.
Optimization methods & software
, 11
(1-4)
, 613-623.
https://doi.org/10.1080/10556789908805765
Identifiers
- DOI
- 10.1080/10556789908805765