The NEOS Server offers DSDP for the solution of semidefinite programming
problems.
The DSDP software package is an implementation of the dualscaling
algorithm for semidefinite programming.
This interiorpoint algorithm has a convergence proof and worstcase
polynomial complexity under mild assumptions on the data. It
provides feasible primal and dual solutions, exploits lowrank structure and
sparsity in the data,
and has low memory requirements compared to other interiorpoint methods.
This implementation of the algorithm can be used as a set of subroutines,
through Matlab, or by reading and writing to data files. Furthermore, it
offers scalable parallel performance for large problems and a
well documented interface.
Some of the most popular applications of semidefinite programming
are model control, truss topology design, and relaxations of combinatorial
and global optimization problems.
Source Code,
binaries, and documentation are available from the
developers
Steve Benson,
and
Yinyu Ye.
DSDP using NEOS
