The Primal-Dual Second-Order Cone Approximations Algorithm for Symmetric Cone Programming

This paper presents the new concept of second-order cone approximations for convex conic programming. Given any open convex cone K, a logarithmically homogeneous self-concordant barrier for K and any positive real number r ≤ 1, we associate, with each direction x ∈ K, a second-order cone K̂r(x) containing K. We show that K is the intersection of the second-order cones K̂r(x), as x ranges through all directions in K. Using these second-order cones as approximations to cones of symmetric positive definite matrices, we develop a new polynomial-time primal-dual interior-point algorithm for semi-definite programming. The algorithm is extended to symmetric cone programming via the relation between symmetric cones and Euclidean Jordan algebras.