In this paper, we present a new primal-dual interior-point algorithm for linear optimization based on a trigonometric kernel function. By simple analysis, we derive the worst case complexity for a large-update primal-dual interior-point method based on this kernel function. This complexity estimate improves a result from El Ghami et?al. (2012) and matches the one obtained in Reza Peza Peyghami et?al. (2014).
['Xin Li', 'Mingwang Zhang']
Interior-point algorithm for linear optimization based on a new trigonometric kernel function