AN ADAPTIVE PRIMAL-DUAL FULL-NEWTON STEP INFEASIBLE INTERIOR-POINT ALGORITHM FOR LINEAR OPTIMIZATION

In this paper, we improve the full-Newton step infeasible interior-point algorithm proposed by Mansouri et al. \cite{Arzani}. The algorithm takes only one full-Newton step in a major iteration. To perform this step, the algorithm adopts the largest logical value for the barrier update parameter $\theta$. This value is adapted with the value of proximity function $\delta$ related to $(x\k y\k s)$ in current iteration of the algorithm. We derive a suitable interval to change the parameter $\theta$ from iteration to iteration. This leads to more flexibilities in the algorithm, compared to the situation that $\theta$ takes a default fixed value. KCI Citation Count: 0