We present a parallelization of the revised simplex method for large extensive forms of two-stage stochastic linear programming (LP) problems. These problems have been considered too large to solve with the simplex method; instead, decomposition approaches based on Benders decomposition or, more recently, interiorpoint methods are generally used. However, these approaches do not provide optimal...

land use optimization using linear programing is a method in watershed management for access to production sustainability and decreasing of soil erosion. the sensitivity analysis of the model can with investigation of results influence form changes in input parameters, lead to decrease the uncertainty in decision-making of management programs. so in this research, linear programming model using...

Two ways for bounding n-variables functions over a box, based on interval evaluations of first order derivatives, are compared. The optimal Baumann form gives the best lower bound using a center within the box. The “admissible simplex form”, proposed by the two last authors, uses point evaluations at n + 1 vertices of the box. We show that the Baumann center is within any “admissible simplex” a...

A variety of pivot column selection rules based upon the gradient criteria (including the steepest edge) have been explored to improve the efficiency of the primal simplex method. Simplex-like algorithms have been proposed imbedding the gradient direction (GD) which includes all variables whose increase or decrease leads to an improvement in the objective function. Recently a frame work has bee...

G eorge Dantzig, in describing the " Origins of the Simplex Method, " 1 noted that it was the availability of early digital computers that supported and invited the development of LP models to solve real-world problems. He agreed that invention is sometimes the mother of necessity. Moreover, he commented that he initially rejected the simplex method because it seemed intuitively more attractive...

This study proposes a novel technique for solving Linear Programming Problems with triangular fuzzy variables. A modified version of the well-known simplex method and Existing Method Solving Interval problems are used linear programming Furthermore, illustration, some numerical examples one real problem to demonstrate correctness usefulness proposed method. The algorithm is flexible, easy, reas...

A lot of research has been done to 1nd a faster (polynomial) algorithm that can solve linear programming (LP) problems. The main branch of this research has been devoted to interior point methods (IPM). The IPM outperforms the Simplex method in large LPs. However, there is still much research being done in order to improve pivoting algorithms. In this paper, we present a new approach to the pro...