16 lines
1 KiB
Markdown
16 lines
1 KiB
Markdown
# DSDP
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[DSDP](https://www.mcs.anl.gov/hs/software/DSDP/) is a free open source
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implementation of an interior-point method for semidefinite programming. It
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provides primal and dual solutions, exploits low-rank structure and sparsity
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in the data, and has relatively low memory requirements for an interior-point
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method. It allows feasible and infeasible starting points and provides
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approximate certificates of infeasibility when no feasible solution exists.
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The dual-scaling algorithm implemented in this package has a convergence proof
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and worst-case polynomial complexity under mild assumptions on the data. The
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software can be used as a set of subroutines, through Matlab, or by reading
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and writing to data files. Furthermore, the solver offers scalable parallel
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performance for large problems and a well documented interface. Some of the
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most popular applications of semidefinite programming and linear matrix
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inequalities (LMI) are model control, truss topology design, and semidefinite
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relaxations of combinatorial and global optimization problems.
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