The Complexity Analysis of an Efficient Interior-Point Algorithm for Linear Optimization

In this paper, an efficient primal-dual interior-point algorithm for large-update methods is introduced by means of a new kernel function. We analysis the complexity of the algorithm and conclude that its iteration bounds, O(n
^3/4
log n/ε), is so far the best complexity result for large-update primal-dual interior-point methods.