This README introduces the Simplex Method, a popular algorithm for solving linear programming problems in R. Linear programming optimizes an objective function, such as maximizing or minimizing a ...

This repository contains a Python implementation of the Simplex algorithm for solving Linear Programming Problems (LPPs). The Simplex algorithm is an iterative method that optimizes a linear objective ...

The simplex method is a practical and efficient algorithm for solving linear programming problems, but it is theoretically unknown whether it is a polynomial or strongly-polynomial algorithm.

Moreover, a new, ratio-test-free pivoting rule is proposed, significantly reducing computational cost at each iteration. Our numerical experiments show that the method is very promising, at least for ...

Gabasov and Kirillova have generalized the Simplex method in 1995 [15] [16] [17] , and developed the Adaptive Method (AM), a primal-dual method, for linear programming with bounded variables.

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse after every step of the method.

A modified version of the well-known dual simplex method is used for solving fuzzy linear programming problems. The use of a ranking function together with the Gaussian elimination process helps in ...

The branch-and-bound method with the revised dual simplex for bounded variables is very effective in solving relatively large-size integer linear programming problems. This paper, based on the general ...

The aim of this paper is to introduce a formulation of linear programming problems involving intuitionistic fuzzy variables. Here, we will focus on duality and a simplex-based algorithm for these ...