When applying the Simplex Method to calculate the minimum coefficient or feasibility condition, if there is a tie for the minimum ratio or minimum coefficient it can be broken arbitrarily. In this instance, at least one basic variable will become zero in the following iteration, confirming that in this instance the new solution is degenerate. […]
The Simplex Method was developed by George Dantzing in 1947. It is without a doubt the most popular algorithm when it comes to solving a Linear Programming (LP) model, and it plays a major role in the introduction to Operations Research (OR). Today we’re presenting a summary of 10 main concepts about the use and […]
The Dual Simplex Method offers an alternative when solving Linear Programming (LP) models with algorithms. This method may be used in particular when the standard way to carry a linear programming model is not available from an initial basic feasible solution. Consider the following LP problem to illustrate the application of the Dual Simplex Method: […]
In this following article we will address properties set by the Fundamental Theorem of Linear Programming through a conceptual discussion and practical and simple examples. These properties are essential when taking into consideration algorithmic resolutions of this kind of mathematical optimization models, among them is what we call the Simplex Method. Every Linear Programming (LP) […]
The Simplex Method is an algorithm that allows us to solve Linear Programming models that sometimes helps us identify exceptional cases with infinite optimal solutions or that the problem is unbounded. In the implementation of the Simplex Method, an unbounded problem is encountered when in any iteration there are any non-basic variables with a negative reduced […]