sdpa-c

The NEOS Server offers SDPA-C (version 6.2.1) for the solution of semidefinite programming problems in sparse SDPA format or in SeDuMi format.

SDPA-C is a software package for solving semidefinite programs (SDP). It is based on a Mehrotra-type predictor-corrector infeasible primal-dual interior-point method. SDPA handles the standard SDP and its dual. It is implemented in C++ utilizing the LAPACK library with ATLAS BLAS as well as the METIS and SPOOLES libraries. It is particularly suited for large sparse problems.

Source and documentation is available here.

SDPA-C was developed by Katsuki Fujisawa, Masakazu Kojima, Kazuhide Nakata, and Makoto Yamashita.

This solver was implemented by Hans Mittelmann and executes at under

Using the NEOS Server for SDPA-C

The user must submit a model in either sparse SDPA or SeDuMi Matlab format to solve a semidefinite programming problem. Examples of models in sparse SDPA format can be found in the SDPLIB library. The same problems in SeDuMi format are here. Other files in this format are at 7th DIMACS Challenge library
Note that when submitting via e-mail or XML-RPC empty tokens need to be deleted

If non-standard parameter settings are required, the user may also submit a parameter file. You can download the default parameter file, edit it and resubmit it as part of the job.

Enter the complete path to the SDPA data file (sparse SDPA format)
SDPA data:

Alternatively, enter the complete path to the SeDuMi format data (Matlab binary, containing At,b,c,K). Note that only linear and semidefinite constraints may be prescribed
SeDuMi data:

Comments:

e-mail address:

Please do not click the 'Submit to NEOS' button more than once.

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