Linear programming is a technique for finding the optimal value of an objective function subject to a set of constraints. The dual simplex method is a variation of the simplex method that can be ...

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 ...

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.

Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the ...

The researchers showed that the simplex method using Tardos' basic algorithm is strongly polynomial for totally unimodular linear programming problems, if the problems are nondegenerate. These ...

This paper works on a modified simplex algorithm for the local optimization of Continuous PieceWise Linear (CPWL) programming with generalization of hinging hyperplane objective and linear constraints ...

The dual simplex method, unlike the standard simplex method, starts with an infeasible but optimal (or better) solution for the objective function in a linear programming problem.

This study proposes a novel technique for solving linear programming problems in a fully fuzzy environment. A modified version of the well-known dual simplex method is used for solving fuzzy linear ...

Discover a novel approach, the primal-dual simplex algorithm, for solving fuzzy linear programming problems without converting them to crisp problems. Overcome limitations of existing methods.