A Constant-Potential Infeasible-Start Interior-Point Algorithmwith Computational Experiments and Applications

Abstract

We present a constant-potential infeasible-start interior-point (INFCP) algorithm for linear programming (LP) problems with a worst-case iteration complexity analysis as well as some computational results.The performance of the INFCP algorithm is compared to those of practical interior-point algorithms. New features of the algorithm include a heuristic method for computing a “good” starting point and a procedure for solving the augmented system arising from stochastic programming with simple recourse. We also present an application to large scale planning problems under uncertainty.