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 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 ...

Abstract 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 ...

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 ...

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 ...

Introducing the Pivot Adaptive Method (PAM) - a faster variant of Gabasov's Adaptive Method (AM) for minimizing computation time. Explore the resolution of problems through successive tables and ...

The simplex method is a fast and efficient algorithm for solving linear programming. Inspired by the optimization method and the simplex method in Seminar 1, this project considers programming the ...

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 ...

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 ...