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 ...

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 ...

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 ...

MATLAB Implementation of the Revised Simplex Method for Linear Programming Hello! If you are here, you are viewing my MATLAB implementation of the Revised Simplex Method. The Revised Simplex Algorithm ...

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 ...

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 ...

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.

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 ...

A computational procedure is given for finding the minimum of a quadratic function of variables subject to linear inequality constraints. The procedure is analogous to the Simplex Method for linear ...