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 ...

However, standard FOMs, such as the primal-dual hybrid gradient (PDHG) method, are not yet reliable for LP problems, solving only a small fraction of instances. Google researchers introduce PDLP ...

Abstract: The goal is to give some theoretical explanation for the efficiency of the simplex method of George Dantzig. Fixing the number of constraints and using Dantzig's self-dual parametric ...

We conclude that the current method is simple, easy, and effective in solving non-linear differential equations, considering that the obtained approximate series solutions are in closed form for the ...

Discover how fuzzy programming methods, such as Chandra Sen's and statistical averaging, can convert multi-objective linear programming problems into single objective functions. Explore numerical and ...

The Simplex method (Simplex Algorithm) is an approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means of finding the optimal solution of an ...

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 ...