A FULL-NEWTON STEP INTERIOR-POINT ALGORITHM FOR SYMMETRIC CONE CONVEX QUADRATIC OPTIMIZATION

In this paper, we present a full-Newton step primal-dual interior-p oint 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 asymmetric cone lies in Euclidean Jordan algebra. The search directions of the algorithm are obt ained from the modification of NT-search direction interms of the quadratic representation in Euclidean Jordan algebra. We prove that the algorithm has a quadratical convergence result. Further more, we present the complexity analys is for the algorithm and obtain the complexity bound as inverted right perpendicular2 root r log mu(0)r/epsilon inverted left perpendicular, where r is the rank of Euclidean Jordan algebras where the symmetric cone lies in.