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 ...

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 ...

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 ...

It is known that the simplex method requires an exponential number of iterations for some special linear programming instances. Hence the method is neither polynomial nor a strongly-polynomial ...

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 ...

Abstract A new variant of the Adaptive Method (AM) of Gabasov is presented, to minimize the computation time. Unlike the original method and its some variants, we need not to compute the inverse of ...

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.

Overview 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 ...

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 ...