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Abstract: . We study the semidefinite programming problem (SDP), i.e the optimization problem of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as is specialized to SDP. Next we present an interior point algorithm which converges to the optimal solution in polynomial time. The approach is a direct extension of Ye's projective method for linear programming. We... (Update)
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BibTeX entry: (Update)
F. ALIZADEH. Interior point methods in semidefinite programming with applications to combinatorial optimization. SIAM Journal on Optimization, 5:13--51, 1995. http://citeseer.ist.psu.edu/alizadeh95interior.html More
@article{ alizadeh95interior,
author = "F. Alizadeh",
title = "Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization",
journal = "SIAM Journal on Optimization",
volume = "5",
number = "1",
pages = "13--51",
year = "1995",
url = "citeseer.ist.psu.edu/alizadeh95interior.html" }
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