The SimplexMethod package provides an efficient implementation of the Simplex Algorithm for solving linear programming (LP) problems. It supports both maximization and minimization of objective ...

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 ...

Learn how to use the dual simplex method to solve linear programming problems when the initial solution is infeasible. Find out how to formulate the dual problem, apply the algorithm, and compare ...

To implement the Simplex Method in R, the following packages are useful: lpSolve: Provides functions for linear programming, including the Simplex Method for optimization problems.; tidyverse: A ...

The simplex method for solving linear programming problems has several advantages over other methods, such as graphical methods, enumeration methods, or interior point methods.

The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear ...

This article introduces the fundamental properties and concepts of linear programming and then presents the simplex algorithm for solving a linear program. The simplex algorithm is implemented using ...

We prove that the classic policy-iteration method [Howard, R. A. 1960. Dynamic Programming and Markov Processes. MIT, Cambridge] and the original simplex method with the most-negative-reduced-cost ...

Abstract: 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 ...