Complexity analysis of an interior-point algorithm for linear optimization based on a new proximity function (Q742844)

The authors propose a new kernel function consisting of a trigonometric function in its barrier term for the large-update primal-dual interior point methods for linear optimization in a large neighborhood of central path. The proximity reduction and the estimation of the step size during an inner iteration are discussed. The worst case iteration complexity for the primal-dual interior point methods based on the new kernel function is derived.