Question
Question: How can linear programming be used in business?...
How can linear programming be used in business?
Solution
In this question we have to explain the benefits or the application of linear programming in the businesses. We will first see how we can graph as linear programming problems mathematically and then we will talk about its application in the business domains.
Complete answer:
In the graphical method, a problem which has multiple variables is solved by drawing the required points on the graph, in graphical problems, these two conditions could arise.
1) Inequality constraints: Some conditions which are expressed in the form of inequalities, the graph is drawn to show us the feasible zone which means that the solution lies on that specific part of the graph. It gives us a range in which the solution lies in.
2) Objective function: The objective function needs to be maximized or minimized. To do this we draw a line which has the same value as that of the objective function and then draw another line parallel to it. Identifying the parallel line to the objective function is the feasible zone. It is the region where the solution will be present.
There can exist two cases, the solution might be a single point on the graph which is called as a generated solution or a segment of multiple points on which the solution exists which is called as the degenerate solution.
Linear programming has always been used in the scientific industries most of which are business oriented. With the help of linear programming the data can be visualized by using the graphs and various relations with variables such as available resources, supply, demand and cost can be visualized.
A single model can be made for all the variables and business decisions and predictions can be made using linear programming.
Note: Linear programming is used generally to find the optimum solution range. It is also to be noted that creation of linear programming will become more intrinsic if the number of variables are increased. It should be mostly used to show the interaction of one variable with the others.