This whole process of operations research is associated with the concept of linear programming. As stated before, Operations Research is associated with allocation of resources in the correct manner so that optimal usage can be made of that resource.

Given that resources are always taken to be scarce, it is imperative that there should be a model on which its allocation be placed so that maximum usage can be made within a limited period of time.

As one of the most important tools of Operations Research, this graphical representation of the data makes linear programming way more operative and acceptable.

So, are you wondering as to how to solve this issue in a graphical manner? There are certain steps to be followed to ensure that correct representation of this data is made.

**Steps to use graphical method in solving this issue of linear programming:**

- Formulation of the problem of linear programming. It is very important that a proper formula is presented that would help in, correct framing of the programming.
- Construction of a graph and plotting of constraint lines. This is the most important factor that needs to be taken into consideration, since it is based on the point on the curve that total programming is placed.
- Check out which side is valid for each of the constraint lines.
- Identify that region which provides the most effective solution.
- Plot the function lines that depict the direction of improvement.
- Check out the actual optimal solution.
- Find out the actual value that is suitable for that solution.

Once these steps are followed in a correct manner, graphical representation becomes lucid and therefore people concerned can deal with this in a better manner.

**Exceptions in a graphical method:**

When a significant topic as Operations Research is taken into consideration, and a tool as Linear Programming is used, there are certain exceptions that are taken into consideration.

- In case it is taken that value of objective function that is obtained is between minimum or maximum, at multiple places at the same time, it is taken that ‘multiple optima’ condition can be obtained.
- At times it so happens that no common ground is present for a particular graph. In such a scenario, it is imperative that the linear programming curve is taken as not acceptable.
- At times it can be seen that ideal solution is obtained at a point that is beyond the usual curve line. It is known as point of infinity and hence the solution that is available is also unbound type.

Thus, by following these steps as well as understanding the exceptions in this method, you can easily get to the base of this programming and use it for multiple purposes.