Pivoting Algorithm for Large Scale Linear Programming with Upper and Lower Bounds

The linear programming (simplified LP) problems in practice are always large scale. Large scale LP demands algorithms with high computing efficiency to satisfy practical needs. Pivoting algorithm for LP can cope with equality constraints, free variables, and constraints with upper and lower bounds efficiently. Especially during the course of computing, the algorithm need not add any auxiliary variables, which can keep the essential form of LP and eliminate the superfluous calculations caused by auxiliary variables. The paper presents the algorithmic steps of pivoting algorithm for LP with upper and lower bounds and demonstrates the process of the algorithm by a simple example.