NCERT Exemplar Class 12 Maths Chapter 12 Linear Programming, are provided here for students to practice and prepare for the exam. Students should have already familiar with the topic of linear inequalities as it was introduced in Class 11 as well. Notably, there are many ways to solve problems based on linear inequalities. However, in class 12, students will further learn about optimisation problems in linear programming problems chapter. Students will also learn to find solutions for these problems using the graphical method.
Class 12 Maths NCERT Exemplar Problems on Linear Programming
The important topics covered in chapter 12 are;
- Linear Programming Problem and its Mathematical Formulation
- Mathematical formulation of the problem
- Graphical method of solving linear programming problems
- Different Types of Linear Programming Problems – Manufacturing problem, Diet problems, Transportation problem.
To help students solve the problems based on Linear Programming, exemplar problems and solutions has been prepared by the experts as per CBSE syllabus. Students can also use the exemplar books as a premier reference tool to know the important topics, study and practice math problems effectively and perform well in the exams.
Students can practice 12th class NCERT solutions for Maths and learn from notes, question papers and other learning materials in the website. Also, students are suggested to solve previous year question papers and sample papers of 12th class Maths subject, to know the question pattern and marking scheme for chapter Linear Programming.
BYJU’S provides class 12th NCERT exemplar for Maths and also updated learning materials for all the classes to make the students prepare for their school exams or board exams and also for competitive exams. These materials could be downloaded for free after registration.
Students are suggested to download BYJU’S- The Learning App and get a more efficient and personalized learning experience with the help of educational videos explaining the concepts of topics like Linear Programming.