# American Institute of Mathematical Sciences

October  2011, 7(4): 891-906. doi: 10.3934/jimo.2011.7.891

## A full-Newton step interior-point algorithm for symmetric cone convex quadratic optimization

 1 Department of Mathematics, Shanghai University, 99, Shangda Road, 200444, Shanghai 2 Department of Mathematics, Shanghai University, Shanghai 200444, China

Received  November 2009 Revised  May 2011 Published  August 2011

In this paper, we present a full-Newton step primal-dual interior-point algorithm for solving symmetric cone convex quadratic optimization problem, where the objective function is a convex quadratic function and the feasible set is the intersection of an affine subspace and a symmetric cone lies in Euclidean Jordan algebra. The search directions of the algorithm are obtained from the modification of NT-search direction in terms of the quadratic representation in Euclidean Jordan algebra. We prove that the algorithm has a quadratical convergence result. Furthermore, we present the complexity analysis for the algorithm and obtain the complexity bound as $\left\lceil 2\sqrt{r}\log\frac{\mu^0 r}{\epsilon}\right\rceil$, where $r$ is the rank of Euclidean Jordan algebras where the symmetric cone lies in.
Citation: Yanqin Bai, Lipu Zhang. A full-Newton step interior-point algorithm for symmetric cone convex quadratic optimization. Journal of Industrial & Management Optimization, 2011, 7 (4) : 891-906. doi: 10.3934/jimo.2011.7.891
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