The practical behavior of the homogeneous self-dual formulations in interior point methods

摘要

Interior point methods proved to be efficient and robust tools for solving large-scale optimization problems. The standard infeasible-start implementations scope very well with wide variety of problem classes, their only serious drawback is that they detect primal or dual infeasibility by divergence and not by convergence. As an alternative, approaches based on skew-symmetric and self-dual reformulations were proposed. In our computational study we overview the implementation of interior point methods on the homogeneous self-dual formulation of optimization problems and investigate the effect of the increased dimension from numerical and computational aspects.