Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization

@article{Benson2000SolvingLS,
  title={Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization},
  author={Steven J. Benson and Yinyu Ye and Xiong Zhang},
  journal={SIAM Journal on Optimization},
  year={2000},
  volume={10},
  pages={443-461}
}
We present a dual-scaling interior-point algorithm and show how it exploits the structure and sparsity of some large scale problems. We solve the positive semideenite relaxation of combinatorial and quadratic optimization problems subject to boolean constraints. We report the rst computational results of interior-point algorithms for approximating the maximum cut semideenite programs with dimension up-to 3000. 
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