Linear programming is the method used in mathematics to optimize the outcome of a function. It is widely used in the fields of Mathematics, Economics and Statistics. In this chapter, we will learn about different types of Linear Programming Problems and the methods to solve them.

- Different Types of Linear Programming Problems
- Graphical Method of Solving Linear Programming Problems
- Linear Programming Problem and Its Mathematical Formulation

**FAQs on Linear Programming**

**Question 1: Explain the use of linear programming?**

**Answer:** Linear programming is useful in obtaining the most optimal solution for a specific problem with specific constraints. Here, formulation of a real-life problem into a mathematical model takes place. It involves an objective function, linear inequalities with subject to constraints.

**Question 2: Explain the components of linear programming?**

**Answer:** The components of linear programming are as follows:

- Decision variables represent quantities whose determination has to take place.
- The objective function shows how the decision variables will impact the cost or value whose optimization has to take place.
- Constraints explain how the decision variables utilize resources that are limited.
- Data quantifies the relationships that are represented in the constraints and the objective function.

**Question 3: Give the disadvantages of linear programming?**

**Answer:** The disadvantages of linear programming are as follows:

- It takes place only with the variables that are linear.
- It does not consider change of variables.
- It cannot solve the nonlinear function.
- Impossible to solve a problem that has more than two variables in the graphical method.

**Question 4: What are the various characteristics of linear programming?**

**Answer:** The characteristics of linear programming are: objective function, constraints, non-negativity, linearity, and finiteness.