Degeneracy in Maximal Clique Decomposition for Semidefinite Programs
Optimization and Control
2016-10-20 v2
Abstract
Exploiting sparsity in Semidefinite Programs (SDP) is critical to solving large-scale problems. The chordal completion based maximal clique decomposition is the preferred approach for exploiting sparsity in SDPs. In this paper, we show that the maximal clique-based SDP decomposition is primal degenerate when the SDP has a low rank solution. We also derive conditions under which the multipliers in the maximal clique-based SDP formulation is not unique. Numerical experiments demonstrate that the SDP decomposition results in the schur-complement matrix of the Interior Point Method (IPM) having higher condition number than for the original SDP formulation.
Cite
@article{arxiv.1509.08021,
title = {Degeneracy in Maximal Clique Decomposition for Semidefinite Programs},
author = {Arvind U. Raghunathan and Andrew V. Knyazev},
journal= {arXiv preprint arXiv:1509.08021},
year = {2016}
}
Comments
15 pages