The NCERT Solutions for Class 12 Maths Chapter 12 Linear Programming prepared by the subject experts at BYJU’S have been provided here. We can say that linear programming is a method to achieve the best outcome in a mathematical model whose requirements are represented by linear relationships. In this chapter students learn about Linear Programming in detail. Solving all the questions from this chapter of the NCERT book of class 12 maths, repeatedly, will help the students in understanding the methods of solving the questions.
The class 12 NCERT solutions of the chapter Linear Programming are very easy to understand as the subject experts at BYJU’S ensure that the solutions are given in simplest form. These NCERT Solutions cover all the exercise questions included in the book and are in accordance with the latest CBSE guidelines.
Access Answers of Maths NCERT Class 12 Chapter 12- Linear Programming
NCERT Solutions for Class 12 Maths Chapter 12- Linear Programming
The major concepts of Maths covered in Chapter 12- Linear Programming of NCERT Solutions for Class 12 includes:
12.2 Linear Programming Problem and its Mathematical Formulation
12.2.1 Mathematical formulation of the problem
12.2.2 Graphical method of solving linear programming problems
12.3 Different Types of Linear Programming Problems
12.3.1 Manufacturing problems
12.3.2 Diet problems
12.3.3 Transportation problems
Exercise 12.1 Solutions 10 Questions
Exercise 12.2 Solutions 11 Questions
Miscellaneous Exercise On Chapter 12 Solutions 10 Questions
NCERT Solutions for Class 12 Maths Chapter 12 – Linear Programming
The chapter Linear Programming itself makes up to a whole unit, Unit Five – Linear Programming, that carries 5 marks of the total 80 marks. There are 2 exercises along with a miscellaneous exercise in this chapter to help students understand the concepts related to Linear Programming thoroughly. Some of the topics discussed in Chapter 12 of NCERT Solutions for Class 12 Maths are as follows:
- A linear programming problem is one that is concerned with finding the optimal value (maximum or minimum) of a linear function of several variables (called objective function) subject to the conditions that the variables are non-negative and satisfy a set of linear inequalities (called linear constraints). Variables are sometimes called decision variables and are non-negative.
- A few important linear programming problems are:(i) Diet problems(ii) Manufacturing problems(iii) Transportation problems
- The common region determined by all the constraints including the non-negative constraints x ≥ 0, y ≥ 0 of a linear programming problem is called the feasible region (or solution region) for the problem.
- Points within and on the boundary of the feasible region represent feasible solutions of the constraints.
- Any point outside the feasible region is an infeasible solution.
- Any point in the feasible region that gives the optimal value (maximum or minimum) of the objective function is called an optimal solution.
- The Theorems that are fundamental in solving linear programming problems.
- If the feasible region is unbounded, then a maximum or a minimum may not exist. However, if it exists, it must occur at a corner point of R.
- Corner point method for solving a linear programming problem.
- If two corner points of the feasible region are both optimal solutions of the same type, i.e., both produce the same maximum or minimum, then any point on the line segment joining these two points is also an optimal solution of the same type
Key Features of NCERT Solutions for Class 12 Maths Chapter 12- Linear Programming
Studying the Linear Programming of Class 12 enables the students to understand the following:
Introduction, related terminology such as constraints, objective function, optimization, different types of linear programming (L.P.) problems, mathematical formulation of L.P. problems, graphical method of solution for problems in two variables, feasible and infeasible regions (bounded or unbounded), feasible and infeasible solutions, optimal feasible solutions (up to three non-trivial constraints).