The dual simplex method is a variation of the simplex method that can be used to solve linear programming problems when the initial solution is infeasible.

The Simplex method (Simplex Algorithm) is an approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means of finding the optimal solution of an ...

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.

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.

Therefore, we propose a dual simplex algorithm to solve these problems. Some fundamental concepts and theoretical results such as basic solution, optimality condition and etc., for linear programming ...

Eventually linear programming came to be used in everything from manufacturing to diet planning. George Bernard Dantzig was born in Portland, Ore., on Nov. 8, 1914.

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 ...