Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization
نویسندگان
چکیده
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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ورودعنوان ژورنال:
- SIAM Journal on Optimization
دوره 10 شماره
صفحات -
تاریخ انتشار 2000