Updated On : November 10, 2023

**Reader's Digest: **Ready for CBSE Class 12 Linear Programming? 🤓 Check out the definition, syllabus, sample questions, & pro prep tips here. ✨

Linear Programming, an integral component of the **CBSE Class 12 Applied Mathematics**, often confuses students.

At the intersection of mathematics and real-world problem-solving, this topic can be your golden ticket to acing the board exams. However, navigating its intricacies demands more than just textbook knowledge.

From understanding the nitty-gritty of the syllabus to strategizing based on weightage and adopting invaluable preparation techniques, success in this topic hinges on a holistic approach.

We will explore various aspects of Linear Programming, including:

**Syllabus of CBSE Class 12 Linear Programming**: A comprehensive overview of what students will learn in this subject.**Linear Programming Weightage**: Understanding the importance of Linear Programming in the board exams.**3 Components of Class 12 Linear Programming**: Breaking down the key elements of a Linear Programming problem.**Study Tips for CBSE Class 12 Applied Math Linear Programming**: Proven strategies for effective preparation.**List of Common Errors While Linear Programming Questions**: Avoiding pitfalls and misconceptions in problem-solving.

Linear Programming (LP) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. It's a technique to optimize a linear objective function subject to linear constraints.

**Example:** Consider a factory that manufactures two products, A and B. To produce one unit of A, 2 hours of machine time and 3 hours of labour time are required.

*For one unit of B, 3 hours of machine time and 1 hour of labour time are required. Let's say in a day, the factory has a maximum of 12 hours of machine time and 9 hours of labour time available. If the profit from each unit of A is $50 and from B is $40, how many units of each product should the factory produce to maximize the profit?*

Let's denote: x = number of units of product A y = number of units of product B

Objective Function (Profit to be maximized): Z = 50x + 40y

Constraints:

- 2x + 3y ≤ 12 (Machine time constraint)
- 3x + y ≤ 9 (Labor time constraint)
- x ≥ 0 and y ≥ 0 (Non-negativity constraints)

Using linear programming, one would plot the constraint inequalities on a graph, identify the feasible region, and then determine which point(s) in that region optimize the objective function. The solution will indicate the number of units of A and B the factory should produce to achieve the maximum profit while staying within its resource constraints.

**Explore More: CBSE Class 12 Applied Maths Algebra**

Linear Programming in CBSE Class 12 Applied Mathematics is an essential mathematical tool used to optimize or find the best possible outcome in various real-life scenarios that can be represented mathematically. Here's a more detailed explanation:

**Optimization**: Linear programming helps in optimizing or maximizing/minimizing an objective function while adhering to a set of linear constraints. The objective function is typically aimed at maximizing profit, minimizing cost, or achieving another goal.**Mathematical Modeling**: Linear programming involves creating mathematical models that represent real-world problems in terms of linear relationships. These linear relationships are often in the form of equations and inequalities.**Linear Relationships**: The essential characteristic of linear programming problems is that the objective function and the constraints are linear. This means that the coefficients of variables in these equations are constants, and the variables themselves are raised to the power of 1 (no squares, cubes, etc.).**Canonical Form**: Linear programming problems can be expressed in canonical form, which includes defining decision variables, formulating the objective function, and setting up linear constraints.**Applications**: Linear programming has a wide range of applications, including but not limited to planning, routing, scheduling, assignment, and design. For example, it can be used in transportation and logistics to find the most cost-effective way to distribute goods or in finance to create an optimal investment portfolio.

The learning outcomes of CBSE Class 12 Linear Programming are designed to equip students with a solid understanding of the key concepts and techniques related to linear programming. Here's a breakdown of the learning outcomes:

**Understand the Linear Programming Problem**: Students should grasp the fundamental concept of linear programming, which involves optimizing an objective function subject to linear constraints. They should be able to recognize situations where linear programming can be applied.**Know the Mathematical Formulation of Linear Programming Problems**: Students should be able to formulate real-world problems into mathematical equations and inequalities that represent linear programming problems. This includes defining decision variables, formulating the objective function, and setting up the constraints.**Conceptualize the feasible region and infeasible region**: Students should be able to distinguish between the feasible region (the set of points that satisfy all constraints) and the infeasible region (the set of points that violate one or more constraints). Understanding these regions is crucial for solving linear programming problems.**Distinguish between the feasible and optimal solutions**: Students should learn to differentiate between feasible solutions (points within the feasible region) and optimal solutions (feasible solutions that optimize the objective function, either maximize or minimize it). They should understand that not all feasible solutions are necessarily optimal.**Find the optimal solution of LPP by Graphical Method**: Students should be proficient in using the graphical method to solve linear programming problems with two variables. This involves graphing the constraints, identifying the feasible region, and finding the optimal solution by analyzing the objective function.**Know the meaning of Optimization**: Students should understand the concept of optimization, which involves finding the best possible solution (maximum or minimum) to a given problem. In linear programming, optimization typically means maximizing profit or minimizing cost while adhering to constraints.

Before you begin the preparation, you must complete the **CBSE Class 12 Applied Maths Syllabus** to know all the essential topics. Some of the topics covered in Linear programming are Constraints, Mathematical Formulation, and Feasible Regions and Graphs.

Let us look at the CBSE Class 12 Linear programming syllabus in detail, and you can plan your preparation accordingly:

- Introduction and related terminologies (constraints, objective function, optimization)
- The mathematical formulation of linear programming problems
- Different types of linear programming problems (Transportation and assignment problems)
- Graphical method of solution for problems in two variables
- Feasible and infeasible regions (bounded and unbounded)
- Feasible and infeasible solutions, optimal feasible solutions (up to three non-trivial constraints)

**Read About: CBSE Class 12 Applied Maths Probability**

While it's true that Linear Programming is an important topic in the CBSE Class 12 Applied Mathematics curriculum, the exact weightage of this topic in the board exams can vary from year to year.

However, it's worth noting that regardless of the specific weightage, it's crucial to thoroughly understand and prepare for Linear Programming as it is a foundational topic in the Applied Mathematics curriculum.

Refer to the weightage below:

Subject |
Periods |
Weightage |

Linear Programming | 25 |
08/80 |

**Check Out: CBSE Class 12 Applied Maths Algebra**

When preparing for the CBSE Class 12 Linear Programming exam, you can expect a range of questions that test your understanding of the concepts and ability to apply them to practical scenarios. Here's what you can generally expect:

**Mathematical Language and Symbolism**: The exam will require you to use mathematical language and symbols to express linear programming problems, formulate objective functions, and write down constraints. It's essential to be comfortable with this aspect of mathematical communication.**Everyday Applications**: Questions may be framed to relate linear programming concepts to everyday experiences. This helps you understand the real-world utility of these mathematical techniques.**Logical Reasoning Skills**: The exam will test your logical reasoning skills as you work through formulating linear programming problems and finding optimal solutions. You'll need to think critically and systematically.**Direct Calculations**: Some questions may be straightforward and ask you to calculate solutions to linear programming problems directly. These could involve finding optimal values of variables or identifying feasible regions.**Complex Situations**: Expect questions that challenge you with complex scenarios. These questions may involve more variables, more constraints, or additional factors that require careful consideration.**Textbook and Reference Examples**: Questions may resemble problems from your textbook exercises or reference book examples. It's essential to practice solving such problems to become familiar with the questions that may appear in the exam.**Algorithm Formation**: You should be prepared to form algorithms and logic for solving linear programming problems. This includes understanding the graphical method, simplex method, and sensitivity analysis.**Additional Concepts**: Besides basic linear programming, the exam may touch on related concepts such as vectors, matrices, and coefficients, especially if they are relevant to the problem.**Applications**: Expect questions that apply linear programming to various fields, including planning, routing, scheduling, assignment, and design. You may be asked to solve problems related to these areas.

**Explore More:** **CBSE Class 12 Applied Maths Basic Financial with Mathematics**

A Linear programming problem (LPP) consists of three important components: (1) Decision variables; (2) The Objective function & (3) The Linear Constraints.

These variables represent the quantities or activities you want to determine in your problem. Decision variables are typically denoted as x, y, z, etc.

They are continuous (can take any real value within a range), controllable (can be adjusted to achieve a goal), and non-negative (they cannot be negative in most cases since negative quantities are often not meaningful in real-world scenarios).

This is a mathematical expression that quantifies the goal of your linear programming problem. It defines what you want to maximize or minimize, such as profit, cost, time, or any other measurable quantity.

The objective function is a linear equation, and it usually takes the form of Z = ax + by, where Z is the value to be maximized or minimized, and a and b are constants.

Constraints represent the limitations or restrictions placed on your decision variables due to resource availability, capacity, or other real-world limitations.

Constraints are expressed as linear inequalities or equations involving the decision variables. They define the feasible region or the set of valid solutions to the problem.

*For example, x + y ≤ 20 represents a constraint that the sum of x and y cannot exceed 20.*

These are typically added to the problem to ensure that the decision variables cannot take negative values, as negative quantities often don't make sense in real-world contexts. In mathematical terms, x ≥ 0 and y ≥ 0 represent non-negative restrictions on the decision variables.

To excel in CBSE Class 12 Linear Programming, you'll need a combination of study materials, including textbooks, reference books, sample papers, and online resources. Here are some recommended study materials to help you prepare effectively:

- Start with the official NCERT (National Council of Educational Research and Training) Class 12 Applied Mathematics textbook. The book comprehensively introduces Linear Programming and is aligned with the CBSE curriculum.

- "Introductory Methods of Numerical Analysis" by S.S. Sastry: This book covers the linear programming topic in a detailed and easy-to-understand manner.
- "Linear Programming and Extensions" by George Dantzig: An advanced reference for those looking to delve deeper into the subject.

- Solve CBSE Class 12 Linear Programming sample papers and previous year's question papers. This will help you understand the exam pattern and practice solving different types of problems.

Follow the list of CBSE Class 12 Linear Programming sample questions provided to you. Let them help you develop a complete idea and understanding of the topics involved before you begin studying them.

The Linear Programming Syllabus mentions that topics under CBSE Class 12 Linear Programming vary from real-life problems to experimental situations. Let us look at some of the sample questions below.

We have provided a few CBSE Class 12 Linear Programming Problems to help you understand the type of questions and knowledge that a Financial Mathematics Exam at Standard XI expects from you.

- Solve the following LPP graphically:
- Maximise Z = 2x + 3y, subject to x + y ≤ 4, x ≥ 0, y ≥ 0
- Solve the following linear programming problem graphically:
- Minimise Z = 200 x + 500 y subject to the constraints: x + 2y ≥ 10; 3x + 4y ≤ 24; x ≥ 0, y ≥ 0
- A manufacturing company makes two types of television sets; one is black and white, and the other is colour. The company has the resources to make at most 300 sets a week. It takes Rs 1800 to make a black and white set and Rs 2700 to make a coloured set. The company can make television sets at no more than Rs 648000 a week. If it makes a profit of Rs 510 per black and white set and Rs 675 per coloured set, how many sets of each type should be produced so the company has a maximum profit? Formulate this problem as an LPP, given that the objective is to maximize the profit.
- A dietician wishes to mix two types of foods in such a way that the mixture contains at least 8 units of vitamin A and 10 units of vitamin C. Food ‘I’ contains 2 units/kg of vitamin A and 1 unit/kg of vitamin C. Food ‘II’ contains 1 unit/kg of vitamin A and 2 units/kg of vitamin C. It costs Rs 50 per kg to purchase Food ‘I’ and Rs 70 per kg to purchase Food ‘II’. Formulate this problem as a linear programming problem to minimize the cost of such a mixture.
- A man rides his motorcycle at a speed of 50 km/hour. He has to spend Rs 2 per km on petrol. If he rides it at a faster speed of 80 km/hour, the petrol cost increases to Rs 3 per km. He has almost Rs 120 to spend on petrol and one hour. He wishes to find the maximum distance that he can travel. Express this problem as a linear programming problem.
- A company receives $20 per book and $18 per calculator in sales. The cost per unit to manufacture each book and calculator is $5 and $4, respectively. The monthly cost must not exceed $27,000 per month if the manufacturing equipment used by the company takes 5 minutes to produce a book and 15 minutes to produce a calculator. How many books and calculators should the company make to maximize profit? Determine the maximum profit the company earns in 30 days.
- A self-employed carpenter pays $90 for the sale of a table and $180 for the sale of a rocking chair. It takes 2 hours for him to make a table and 5 hours to manufacture a rocking chair. He is limited to working 40 hours per week. The average manufacturing cost is $15 per table and $45 per rocking chair. He wishes to keep his manufacturing cost at $ 315 per week. How many tables and rocking chairs should he make to maximize weekly sales? Determine the maximum sales and profit he can make per week.
- Some students want to start a business that cleans and polishes cars. It takes 1.5 hours of labour and costs $2.25 in supplies to clean a car. It takes 2 hours of labour and costs $1.50 in supplies to polish a car. The students can work a total of 120 hours a week. They also decide to spend no more than $ 135 weekly on supplies. The students expect to make a profit of $ 7.75 for each car they clean and $ 8.50 for each car they polish. What is the maximum profit the students can make?
- A factory makes tennis rackets and cricket bats. A tennis racket takes 1.5 hours of machine time and 3 hours of craftsman’s time in its making, while a cricket bat takes 3 hours of machine time and 1 hour of craftsman’s time. The factory is available in a day for not more than 42 hours of machine time and 24 hours of craftsman’s time.

(i) What number of rackets and bats must be made if the factory is to work at total capacity?

(ii) If the profit on a racket and a bat is Rs 20 and Rs 10, respectively, find the maximum profit of the factory when it works at full capacity.

**Read About:** **CBSE Class 12 Applied Maths Inferential Statistics**

Preparing for CBSE Class 12 Applied Mathematics Linear Programming requires a structured approach and consistent effort. Here's a more detailed preparation strategy to help you score well:

**Understand the Syllabus**: Familiarize yourself with the CBSE Class 12 Linear Programming syllabus. This will help you identify the topics you must cover and effectively allocate your study time.**Create a Study Plan**: Develop a study schedule covering all the syllabus topics. Allocate more time to challenging areas or topics you find difficult. Stick to your study plan consistently.**Use Real-Life Examples**: As mentioned, relate the concepts to real-life examples and situations. This not only helps in understanding but also makes the subject more interesting. Try to find practical applications of linear programming in daily life.**NCERT Textbook**: Start with the NCERT textbook. Read it thoroughly and understand the concepts and solved examples. NCERT is the foundation, and a strong grasp of these basics is essential.**Reference Books**: After you've mastered the NCERT textbook, you can move on to reference books for more practice and advanced problems. Some good reference books have been mentioned in a previous response.**Practice, Practice, Practice**: Practice is the key to success in mathematics. Solve various problems from various sources, including your textbook, reference books, and online resources. Pay attention to different types of problems and scenarios.**Previous Year Papers**: Solve previous year question papers and sample papers. This will help you understand the exam pattern, the questions asked, and the time management required during the exam.**Pen and Paper Practice**: As much as possible, solve problems manually without relying on calculators. This will improve your calculation skills and mental math abilities.**Self-Assessment**: Regularly assess your progress by taking self-assessment tests or quizzes. Identify your weak areas and work on improving them.**Clarify Doubts**: Don't hesitate to ask your teachers or peers for help if you have doubts or face challenges with specific concepts. Clearing doubts promptly is crucial for a strong foundation.

**Find Out: **CBSE Class 12 Applied Maths Numerical Applications

Here's a table summarizing common errors made by students in CBSE Class 12 Applied Mathematics Linear Programming and tips on how to avoid them:

Common Errors | How to Avoid Them |
---|---|

Not understanding the problem statement | Read the problem statement carefully and identify the objective, constraints, and variables involved. Make sure you have a clear understanding of what the problem is asking. |

Incorrect formulation of constraints | Double-check the constraints you have written to ensure they accurately represent the problem. Pay attention to inequalities, signs, and units of measurement. |

Failing to identify the feasible region | Graphically represent the constraints to identify the feasible region correctly. Avoid errors in plotting points and lines on the graph. |

Misinterpreting the objective function | Be sure to understand whether the objective is to maximize or minimize, and correctly write the objective function. Mistakes here can lead to incorrect solutions. |

Incorrectly solving linear programming problems. | Follow the steps of the graphical method or simplex method systematically. Avoid arithmetic errors when performing calculations. |

Not considering non-negativity constraints. | Linear programming often involves non-negativity constraints, where variables cannot be negative. Ensure you include these constraints when necessary. |

Ignoring the sensitivity analysis | Forgetting to perform sensitivity analysis can lead to missed opportunities for improvement. Always analyze changes in coefficients and constraints to understand their impact on the optimal solution. |

Not labelling variables and points on graphs. | Properly label variables, coordinates, and points on graphs to avoid confusion. Clarity in labelling is crucial for a correct solution. |

Rushing through practice problems | Take your time to solve practice problems carefully. Rushing can lead to errors that you might miss during revision. |

Lack of revision and self-assessment | Regularly revise concepts, formulas, and techniques. Self-assessment through quizzes and practice tests helps identify weak areas and rectify mistakes. |

Not seeking help when needed. | If you're stuck or confused about a concept or problem, don't hesitate to seek help from your teacher, classmates, or online resources. |

In conclusion, Linear Programming in CBSE Class 12 Applied Mathematics is a crucial mathematical tool with diverse applications in real-life scenarios.

This blog has provided valuable insights into the subject, covering its definition, practical applications, learning outcomes, syllabus, weightage, and exam expectations. Key takeaways include:

*Linear Programming is a method to optimize linear objective functions within linear constraints.**It finds applications in fields like finance, logistics, and manufacturing.**Learning outcomes encompass understanding problem formulation, feasible regions, and optimization.**The syllabus covers mathematical formulation, types of problems, graphical solutions, and feasible regions.**Practising with sample questions and previous papers is essential for success.**Avoiding common errors involves careful problem analysis, precise formulation, and systematic solution methods.*

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