Description: Based on the change of , an augmented lagrangian algorithm to solve convex quadratic SDP is proposed. The algorithm’s distinguishing feature is a factorization, the gradient method and an exact linesearch procedure. The convergence of the algorithm is shown. Numerical experiments show that our methods are efficient and robust.
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NLPforCQSDP\barparameter.m
...........\coefficient.m
...........\generateDATE.m
...........\genparameter.m
...........\gradient.m
...........\linesearch.m
...........\main1.m
...........\qsdpAL.m
...........\residual.m
...........\v0.m
NLPforCQSDP
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