A class of methods of admissible directions for linear programming

A new class of linear programming algorithms is proposed. They differ from simplex and reduced gradient methods by a systematic use of inner, or strictly admissible search directions. The purpose is to implement the idea that one step along a search direction pointing to the relative interior of the admissible set can spare many steps along its relative boundary. Finiteness of the algorithms is proved and some computational aspects are discussed.