Methods of dual simplex type for linear optimization problems of flow

In this paper we study the linear optimization problem lower and upper constrained (i.e., there are lower and upper bounds on constraints and variables) and develop dual simplex methods that explore the dual problem, which is piecewise linear, in some sense nonlinear. Different one-dimensional searches were examined. Computational experiments showed that the exact one-dimensional search in the dual simplex direction has the best performance.