On the Step Choice in Projection Algorithms for Large-Scale Linear Programming Problems

In order to solve large-scale linear programming problems the group of algorithms with projection of a point onto the set is considered. Special method for selecting the initial approximation and the step-size parameters is given to reduce computational time. Comparative analysis of the rates of convergence and running time of the algorithm with various step parameters is done for the special large-scale test problem with randomly generated data.