A novel kernel function bridging iteration bounds in interior-point algorithms for linear programming
Kernel functions play an important role in designing and analyzing interior-point methods. They are not only used for determining search directions but also for measuring the distance between the given iterate and the -center in the algorithms. Currently, interior-point methods based on kernel functions are among the most effective methods for solving different types of optimization problems and are very active research area in mathematical programming. Therefore, in this work, we introduce a novel...