Solving semidefinite programming problems via alternating direction methods

Citations of this article
Mendeley users who have this article in their library.


In this paper, we consider an alternating direction algorithm for the solution of semidefinite programming problems (SDP). The main idea of our algorithm is that we reformulate the complementary conditions in the primal-dual optimality conditions as a projection equation. By using this reformulation, we only need to make one projection and solve a linear system of equation with reduced dimension in each iterate. We prove that the generated sequence converges to the solution of the SDP under weak conditions. © 2005 Elsevier B.V. All rights reserved.




Yu, Z. (2006). Solving semidefinite programming problems via alternating direction methods. Journal of Computational and Applied Mathematics, 193(2), 437–445.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free