A Polynomial-time Interior-point Algorithm for Convex Quadratic Semidefinite Optimization
Mathematics, Shanghai University, Shanghai, 200444, P.R. China. firstname.lastname@example.org
Accepted: 1 September 2010
In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, O( log ), which is best-known bound so far.
Mathematics Subject Classification: 90C05 / 90C51
Key words: Convex quadratic semidefinite optimization / interior-point algorithm / small-update method / iteration bound / polynomial-time
© EDP Sciences, ROADEF, SMAI, 2010