RD Sharma Class 12 Solutions Chapter 30 - Linear programming (Ex 30.2) Exercise 30.2

RD Sharma Solutions for Class 12 Maths Chapter 30 Exercise 30.2 Linear Programming are provided here for the benefit of students. Students from CBSE, ICSE or other government board exams prefer RD Sharma Books to prepare for exams and other tests such as job entrance exams and various courses. The RD Sharma Class 12 solutions are specially designed by Vedantu’s team of experts.

Students can use these solutions to overcome the fear of solving maths and the solutions are designed in such a way that the students can find simple ways to solve different problems. These solutions can help students to refine their learning and problem-solving skills. Students can go through the RD Sharma solutions for class 12 chapter 30 Linear Programming Exercise 30.2 below and it will be beneficial for them.

Different Types of Linear Programming in RD Sharma Class 12 Solutions Chapter 30 - Linear programming (Ex 30.2) Exercise 30.2 - Free PDF

Different types of problems in the direct planning problem are included in the ideas of the 12th class. Of course:

(I) Production Problem - Here we increase profits with the help of less resource use.

(II) Eating Disorders - We determine the number of different nutrients in food to reduce production costs.

(III) Transportation Problem - Here we determine the plan to find the cheapest way to transport a product in a short time.

Some Important Terms of Linear Programming That You Should Know

There are certain words used in the construction and resolution of consecutive planning problems. Let's explain some of the keywords we will use here:

• Objective Function: The linear function of the Z = ax + by form, where a and b are constant, which should be reduced or enlarged is called the linear objective function.

Consider for example, Z = 175x + 150y. This is the function of the line object. The variables x and y are called resolution variables.

• Constraints: The linear inequalities or equations or limitations of LPP variables (Linear programming problems) are called constraints. Circumstances x ≥ 0, y ≥ 0 are called non-negative constraints.

For example, 5x + y ≤ 100; x + y ≤ 60 are obstacles.

• Optimization Problem: A problem that seeks to increase or decrease linear function (say with two variables x and y) under certain constraints as determined by linear inequality set is called an optimization problem. Linear programming problems are special types of optimization problems.

• Feasible Region: A feasible region determined by all given constraints including non-critical barriers (x ≥ 0, y ≥ 0) of the linear programming problem is called the potential region (or feasible region) of the problem. The region beyond the feasible region is called an infeasible region.

• Feasible Solutions: These are the points within and in the scope of the space that may represent feasible solutions to the issues. Any point outside of a feasible area is called an infeasible solution.

• Optimal (or feasible) Solution: Any point in a feasible region that provides the total amount (maximum or minimum) of the objective function is called the optimal solution.