The NCERT Solutions for Class 12 Maths Chapter 12 - Linear Programming can now be downloaded from the MSVgo website. The solutions are carefully curated by experts in the industry and therefore make for reliable study material. Students can rest assured that all the important topics under the Class 12 Linear Programming chapter are covered in detail, with step-by-step answers for exercise questions that will come in handy if the student has any difficulty while solving a problem. Furthermore, solving questions from the Class 12 Maths NCERT Solutions ensures that the students’ learning is aligned with the curriculum, thus preparing them for the exams. Download the solutions to familiarise yourself and be confident in the chapter.
Topics Covered in Chapter 12 Linear Programming
1. Introduction
2. Linear Programming Problem and its Mathematical Formulation
3. Different Types of Linear Programming Problems

In previous classes, linear inequalities and systems of linear equations with two variables and solving them using the graphical method were covered. The NCERT Solutions for Class 12 Maths Chapter 12 covers the necessary topics related to linear programming, such as definitions, rules of linear programming, how to plot linear equations on a graph, methods to solve linear programming problems, how to apply linear programming to real-world problems, and several solved examples to ensure that students get rigorous practice in solving exam-style questions.

Linear programming solves problems of optimising (either maximising or minimising) a linear function that has certain conditions, which can be equalities or inequalities. Linear programming is used to obtain a feasible region such that the highest or lowest value of the function is the optimised solution to the problem.

Here are some rules of linear programming:

__Constraints__: The constraints should be defined in mathematical form.__Objective function__: The objective function should be defined in quantitative terms.__Linearity:__The relationship between the variables in the function should be linear, which means that the degree of the variable should be one.__Finiteness:__The number of input and output numbers should be finite. An optimal solution is not feasible if there are infinite variables in a function.__Non-negativity:__The value of the variables cannot be negative. In real-world problems, quantities usually do not have negative values, hence only positive values are taken.__Decision variables__: The decision variable gives the ultimate solution to the problem. Hence, identifying the decision variables is necessary while solving the problem.

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