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) […]

## Formulating and Solving a Capacity Allocation Problem of a Plane

The passenger transport industry faces the problem of determining how to efficiently allocate transportation capacity when offering different prices or fees to their customers for a specific route. This is why they must consider sales revenues associated with each type of rate, estimated customer demand for such fees and the capacity of the transport in […]

## How to Download and Install the Trial version of Premium Solver Pro in Excel 2010

Solver is definitely next What’sBest! The most popular tool for solving optimization models using Microsoft Excel as a platform. In fact the free version of Solver we use is developed by Frontline Systems Inc., which provides a number of tools and resolution engines that are very useful when addressing problems of real life situations that […]

## Primal Dual Relationships in Linear Programming (Duality Theory in LP)

The dual model of a Linear Programming problem consists of an alternative modeling instance that allows us to recover the information of the original problem commonly known as primal model. Therefore it is sufficient to solve one of them (primal or dual) to obtain the optimal solution and the optimal value of the equivalent problem […]

## Complementary Slackness Theorem (Duality Theory in Linear Programming)

One of the major theorems in the theory of duality in Linear Programming is the Complementary Slackness Theorem. This theorem allows us to find the optimal solution of the dual problem when we know the optimal solution of the primal problem (and vice versa) by solving a system of equations formed by the decision variables […]