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NCERT exemplar Class 12 Maths solutions chapter 12 Linear Programming - If you often wonder what the best solution to a set of problems would be, then linear programming would help you. It is the process of achieving the best possible outcome of a mathematical model. Explore the detailed concepts in NCERT exemplar Class 12 Maths chapter 12 solutions. Students looking for NCERT Exemplar Class 12 Maths solutions chapter 12 PDF download can use the ‘Save as webpage’ feature in the browser.
Also, read - NCERT Class 12 Maths Solutions
Question:1
Determine the maximum value of subject to the constraints:
Answer:
Given that:
It is subject to constraints
Now let us convert given inequalities into equation.
We obtain following equation
The lines that represent 2x+y=6, then further meet the other axes respectively in order to get an answer. The points are to be joined to obtain the line 2x+y=6. It is then further clarified that the equation is satisfied. Then the region that contains the origin is then represented by the set of solutions of the inequation
The region represented by
The line which is parallel to the Y-axis then meets the X-axis which comes at X=2. Hence, it is clarified that (0,0) satisfies the inequation.
After plotting the equation graphically, we get an answer:
Coming to the conclusion, when we substitute the values in Z at the corner points, we get the following answer:
Therefore, the final answer is the maximum value of Z is 42 at the point (0,6).
Question:2
Maximise , subject to the constraints:
Answer:
Following is the answer
It is subject to constraints
Now let us convert the given inequalities into equation.
We obtain the following equation
The part represented by
One of the lines that is x+y=1 meets the axes (0,1) and (1,0) respectively. Then the lines are joined to obtain the line that is x+y=1. Therefore, it is clear that (0,0) the equation satisfies
The region that is represented by is first quadrant, and further satisfies these inequations. The graphic plotting is given below:
The shaded region OBC shows the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.
Corner Points are
When we substitute the values in Z, we get the following answer
Hence, the maximum value of Z is 4 at the point (0,1).
Question:3
Maximize the function , subject to the constraints:
Answer:
It is subject to constraints
Now let us convert the given inequalities into equation
We obtain the following equation
The region represented by x≤3:
The line is parallel to the Y-axis and then meets the X-axis at the point x=3. Then it further gives a clarification that it satisfies the inequation in the problem that is. The region then represents the origin and the set of the inequation
The region that is represented by
The line that is parallel to the x-axis meets the y-axis. The part that contains the region represents the solution set of the other inequation
Therefore, the region that represents the is first quadrant and satisfies the inequations. After plotting the graph we get
The shaded region OBCD is the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.
Corner Points are
Now we will substitute these values in Z at each of these corner points, we get
Therefore, the final answer is that the value of Z is 47 at the point of (3,2).
Question:4
Minimise subject to the constraints:
Answer:
It is given that:
It is subject to constraints
Now let us convert the given inequalities into equation
We obtain the following equation
The region which is represented by
The line in the sum meets the coordinate axes (7,0) and (0,7) respectively. If we join the lines, we will get the other line that is x + y =7. And then it is further clear that (0,0) satisfies the inequation. Then the origin represents the solution for the set of the inequation
The region represented by
The line 2x-3y+6=0 collides with the other axes to coordinate (-3,0) and (0,2) respectively. Then the lines are joined further to obtain the line 2x-3y+6=0. So, the part that contains the origin then represents the other solution set of the inequation
Looking at the graph we get,
The shaded region OBCD is the feasible region is bounded, so, minimum value will occur at a corner point of the feasible region.
Corner Points are O(0,0), B(0,2), C(3,4) and D(7,0)
Now we will substitute these values in Z at each of these corner points, we get
So, the final answer of the question is the minimum value of Z is -30 at the point of (0,2).
Question:5
Determine the maximum value of if the feasible region (shaded) for a LPP is shown in Fig.12.7.
Answer:
From the question, it is given that
The figure that is given above, from that we can come to a constraint that
Now let us convert the given inequalities into equation
We obtain the following equation
The region represented by
We can say that the line meets the coordinate axes (76,0) and (0,38) respectively. When we join the points to further get the required line we get the line . Then, we can say that it is clear that (0,0) satisfies the inequation . And then origin is represented by the solution set of inequation
The region represented by
The line that has 2x +y=104 then meets the other coordinate axes (52,0) and (0,104) simultaneously. Then we need to join the points to get the result of 2x +y=104. The origin then represents the solution set further of the inequation
The first quadrant of the region represented is
The graph of the equation is given below:
The shaded region ODBA is the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.
Corner Points are O(0,0), D(0,38), B(44,16) and A(52,0)
Now we will substitute these values in Z at each of these corner points, we get
Hence, the maximum value of Z is 196 at the point (44,16)
Question:6
Feasible region (shaded) for a LPP is shown in Fig. 12.8. Maximise
Answer:
Following is the equation:
Z=5x+7y
The region that is shaded is OABD in the diagram that is being given. The maximum value of the corner point will occur at the feasible point.
When we substitute these values in Z, we get the corner points, we get:
Therefore, the final answer is the maximum value of Z is 43 at the point (3,4)
Question:7
The feasible region for a LPP is shown in Fig. 12.9. Find the minimum value of
Answer:
The following is given that:
It is subject to constraints
Now let us convert the given inequalities into equation
We obtain the following equation
The region represented by x + y ≤ 5:
The line that shows , then meets the axes that coordinate (5,0) and (0,5) respectively. We need to join the points in order to obtain the line . Hence, it is clarified that (0,0) then satisfies the inequation . Therefore, the region that has the origin represents the solution set of .
The region that is represented by
The line that is meets the coordinate axes (9,0) and (0,3) respectively to get the final answer. When we join the points we get the line . Therefore, it is then clear that the region doesn’t contain the origin and represents the solution set of the inequation.
The graph is further given below:
The shaded region BEC is the feasible region is bounded, so, minimum value will occur at a corner point of the feasible region.
Corner Points are B(0,3), E(0,5) and C(3,2)
Now we will substitute these values in Z at each of these corner points, we get
Hence, the minimum value of Z is 21 at the point (0,3)
Question:8
Refer to Exercise 7 above. Find the maximum value of Z.
Answer:
It is given below that:
The figure that is given above, we can see the subject to constraints
Now let us convert the given inequalities into equation
We obtain the following equation
The region which represents is explained below:
The line that is x+y=5, when meets the coordinate axes we get (9,0) and (0,3) respectively. After joining these points, we get the further line that is x+3y=9. The region does not represent the solution set.
The region that represents the first quadrant is
The graph for the same is given below:
The shaded region BEC is the feasible region is bounded, so, minimum value will occur at a corner point of the feasible region.
Corner Points are B(0,3), E(0,5) and C(3,2)
Now we will substitute these values in Z at each of these corner points, we get
Question:9
Answer:
It is subject to constraints
Now let us convert the given inequalities into equation
We obtain the following equation
The region representing
The line that is meets the other coordinate axes (4,0) and (0,2) respectively. Once we join these points we get the result . After joining the lines, it is then clarified that it does not satisfy the inequation . So, then the region that does not contain the origin then represents the set of solutions.
The region that is represented by
The other line that is meets the coordinate axes (3,0) and (0,3) respectively. When we join these points we obtain the line . It is then cleared that it does not satisfy the inequation. Therefore, the region that does not contain the origin further represents the solution set.
Region represented by is first quadrant, since every point in the first quadrant satisfies these inequations
The graph of these equations is given.
The shaded region ABC is the feasible region is bounded, so, minimum value will occur at a corner point of the feasible region.
Corner Points are A(0,3), B(2,1), and C(4,0) .
When we see the region, we can see that it is unbounded, and 3 is not the minimum value of Z.
When we decide this issue, we can graph the inequality 4x + y < 3 and then further check that whether the resulting does has the open half no point in common, otherwise Z has no minimum value.
The graph that is shown above, we can see that it is clear that there is no point in common with the region and therefore, Z has a minimum value of 3 at (0, 3).
Henceforth, the minimum value of Z is 3 at the point (0, 3).
Question:10
Answer:
It is given that:
The figure that is given above, from that we can see that the shaded region is feasible and is bounded, so the maximum and the minimum point will occur at the corner point.
Question:11
Answer:
We can assume that the manufacturer produces x units of type A circuits and y units of type B circuits. We have made the following table from the data that is given to us:
From the table, we can see that the profit becomes,
The constraints that we got, i.e. the subject to the constraints,
[this is resistor constraint]
When we divide it throughout by 10, we get:
And [this is transistor constraint]
After that when we divide it through 10, we get
And [non-negative constraint]
So, the maximum profit is
subject to
Question:12
Answer:
Let us consider that the firm has X number of large vans and Y number of small vans . We have made the following table:
Looking at the table, we can see that the cost becomes Z=400x+200y.
Now when we minimize the cost, i.e. minimize
The subject to constraints are:
When we divide it by 40, we get:
Now will divide throughout by 200, we get
Also given the number of large vans cannot exceed the number of small vans
And [non-negative constraint]
So, minimize cost we have to minimize subject to
Question:13
On selling these screws, the company gets a profit of Rs 100 per box on type A screws and Rs 170 per box on type B screws.
Formulate this problem as a LPP given that the objective is to maximise profit.
Answer:
Let’s assume that the company manufactures X boxes of type A screws and Y boxes of type B screws. Look at the following table:
According to the table, we can see that profit becomes
Now, we have to maximize the profit, i.e., maximize
The constraints so obtained, i.e., subject to the constraints,
[time constraints for threading machine]
Now will divide throughout by 2, we get
And [time constraints for slotting machine]
And [non-negative constraint]
So, to maximize profit we have to maximize subject to
Question:14
Answer:
Let’s take an assumption that the company manufactures x number of type A sweaters and y number of type B. We have made a table for your understanding which is given below:
If we look at the table, we can see that the profit becomes
If we have to maximize the profit, then maximize
The constraints so obtained, i.e., subject to the constraints,
The company spends at most Rs 72000 a day.
Divide throughout by 120, we get
Also, company can make at most 300 sweaters.:
Also, the number of sweaters of type B cannot exceed the number of sweaters of type A by more than 100
.....(iii)
And [non-negative constraint]
So, to maximize profit we have to maximize subject to
Question:15
Answer:
If we see the man rides his motorcycle for a distance of X km at a speed of 50km/hr then he will have to spend Rs.2 per km for petrol.
If we assume that the man rides his motorcycle for a distance of Y km at a speed of 80km/hr, then he will need to spend Rs.3 per km on petrol.
Assuming that he has to spend Rs.120 on petrol for a total distance so the constraint becomes,
Now also given he has at most one hour's time for total distance to be covered, so the constraint becomes
Now taking the LCM as 400, we get
..........(ii)
And [non-negative constraint]
He want to find out the maximum distance travelled, here total distance,
Now, we have to maximize the distance, i.e., maximize
So, to maximize distance we have to maximize, , subject to
Question:16
Answer:
If we refer to Exercise 11, we get the following information.
The manufacturer produces X units of type A circuits and y units of type B circuits. We make the following table from the given data:
Looking at the table, we can see that profit becomes .
When we maximize the profit, i.e. maximize .
If we see at the constraints that we have obtained, then the subject to constraints,
[this is resistor constraint]
Dividing it throughout by 10, we get the answer as:
And [this is transistor constraint]
Dividing it by 10 throughout we get
And [this is capacitor constraint]
Then divide it by 10, we get
And [non-negative constraint]
So, when we look at the maximize profit it is , subject to
When we convert it to equation, we get the following equation
The region that is represented by :
When the line meets the coordinate axes (10,0) and (0,20) respectively. Once after the lines are joined, we obtain the line . It is clear that (0,0) satisfies the inequation . So the region then represents the set of solutions.
The region represented by :
Once the line meets the coordinate axes (12,0) and (0,6) respectively, then the points are joined to get the final result that is . It is then clear that it satisfies the inequation and the region does not contain the origin.
The region represented by
The line then meets the coordinate axes (15,0) and (0,5) respectively. Once we join these points we obtain the line . It is clear that (0,0) satisfies the inequation x+3y≤ 15. So the region that contains the origin represents the solution set of the inequation .
Region represented by x≥0 and y≥0 is first quadrant, since every point in the first quadrant satisfies these inequations
The graph of the same is given below:
The shaded region OABCD is the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.
Corner Points are O(0,0), A(0,5) , B(6,3), C(9.3,1.3) and D(10,0)
Now we will substitute these values in Z at each of these corner points, we get
So from the above table the maximum value of Z is at point (9.3,1.3), but as the manufacturer is required to produce two type of circuits, so the parts of resistors, transistors and capacitors cannot be decimals. So we will consider the next maximum number.
Hence, the maximum value of Z is 480 at the point (6,3) i.e., the manufacturer should produce 6 circuits of type A and 3 circuits of type B so as to maximize his profit.
Question:17
Refer to Exercise 12. What will be the minimum cost?
Answer:
We get the following information referring to the exercise 12:
Let us consider that the firm has X number of large vans and Y number of small vans . We have made the following table:
According to the table, the cost becomes .
When we have to minimize the cost, i.e., minimize .
The subject to the constraints are as follows:
Then divide it by 40, we get
Then divide it by 200, we get
The number of the vans that are large exceed the number of small vans
So, when we minimize cost we have to minimize, Z=400x+200y, subject to
When we convert the inequalities into equation, we get the following equation
We can see the region represented by :
The line that is when it meets the coordinate axes (6,0) and (0,15) respectively we get the desired answer. We will then join these points to obtain the line 5x+2y=30. It is clear that (0,0) does not satisfy the inequation . So the region that does not contain the origin represents the solution set of the inequation .
The region that represents :
We can see that the line meets the coordinate axes (7.5,0) and (0,15) respectively. We will have to join these points to obtain the line . It is clear that (0,0) satisfies the inequation . So the region that contains the origin represents the solution set of the inequation .
The region represented by x≤y:
Then when the line x=y is a line that passes through the origin and doesn’t touch any coordinate axes at any other point except (0,0). When we join the points we get line x=y.
Region represented by x≥0 and y≥0 is first quadrant, since every point in the first quadrant satisfies these inequations
The shaded region ABC represents the feasible region is bounded, and minimum value will occur at a corner point of the feasible region.
Now we will substitute these values in Z at each of these corner points, we get
So from the above table the minimum value of Z is at point
Hence, the minimum cost of the firm is Rs. 2571.43
Question:18
Answer:
Refer to the Exercise 13, we get the following data:
Let us assume that the company manufactures x boxes of type A screws and y boxes of type B screws. We make the following table from the given data:
Type A screws (x boxes) | Type B screws (y boxes) | Max time available on each machine in a week | |
Time required for screws on threading machine | 2 | 8 | 60 hrs = 60*60min = 3600min |
Time required for screws on slotting machine | 3 | 3 | 60 hrs = 60*60min = 3600min |
Profit | Rs 100 | Rs170 |
When we look at the table, the profit becomes, Z=100x+170y
Thus according to the table, the profit becomes, Z=100x+170y
The constraints that we have obtained that is subject to constraints:
[time constraints for threading machine]
Divide it throughout by 2, we get
And [time constraints for slotting machine]
…………..(ii)
And x≥0, y≥0 [non-negative constraint]
So, to maximize profit we have to maximize, Z=100x+170y, subject to
Now let us convert the given inequalities into equation.
We obtain the following equation
The region that represents x+4y≤ 1800:
We can say that the line meets the coordinate axes (1800,0) and (0,450) respectively. When we join these points, we get the desired line that is . We can say that it is clear that it satisfies the inequation and therefore the region that contains the origin further represents the set of solutions of the inequation.
The region represented by :
The line further meets the axes (1200,0) and (0,1800) respectively. After joining these points, we get the result that is . It is then clear that it satisfies the inequation . So the region that contains the origin represents the solution set of the inequation .
The graph is given below:
The shaded region OBCD is the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.
Corner Points are O(0,0), B(0,450), C(1080,180) and D(1200,0)
Now we will substitute these values in Z at each of these corner points, we get
So from the above table the maximum value of Z is at point (1080,180) .
Therefore, the final answer is maximum profit to the manufacturer is Rs.
1,38,600
Question:19
Answer:
When we refer to the exercise, we get the following information:
Let’s take an assumption that the company manufactures x number of type A sweaters and y number of type B. We have made a table for your understanding which is given below:
Thus according to the table, the profit becomes, Z=200x+120y
If we have to maximize the profit, i.e., maximize Z=200x+120y
The subject to constraints is:
The company spends at most Rs 72000 a day
.
Divide throughout by 120, we get
Also, company can make at most 300 sweaters.:
Also, the number of sweaters of type $B$ cannot exceed the number of sweaters of type A by more than 100
i.e.,
And [non-negative constraint]
So, when we convert the inequalities into the equation we get the following answer:
We can say that the line 3x+y=600 meets the coordinate axes (200,0) and (0,600) respectively. Once the points are joined, we get the answer that is 3x+y=600. It is justified that 3x+y≤ 600. So the region that contain the origin represents the solution set of the inequation 3x+y≤ 600
The region represented by x+y≤ 300:
The line when it meets the coordinate axes respectively that is y= 100+x meets (-100,0) and (0,100) respectively and when the lines are joined we get the line y= 100+x. Then it is clarified that it satisfies the inequation. Therefore, the region contains the origin that represents the solution of sets of inequation.
The graph of the same is given:
The shaded region OBCDE is the feasible region is bounded, so, minimum value will occur at a corner point of the feasible region.
Corner Points are O(0,0), B(0,100), C(100,200) , D(150,150) and E(200,0)
Now we will substitute these values in Z at each of these corner points, we get
Hence, the final answer is the maximum profit to the manufacturer is Rs. 48,000, for making 150 sweaters each of type A and type B.
Question:20
Refer to Exercise 15. Determine the maximum distance that the man can travel.
Answer:
When we refer to the Exercise, we get the following information:
If the man rides his motorcycle for a distance of x km at a speed of 50km/hr then he has to spend Rs. 2/km on petrol.
And if he rides his motorcycle for a distance of y km at a speed of 80 km/hr then he has to spend Rs. 3/km on petrol.
He has Rs.120 to spend on petrol for covering the total distance so the constraint becomes
2x+3y≤120…………(i)
Given that he has only one hour’s time to cover the total distance, then the constraint becomes
{as distance speed x time}
Now taking the LCM as 400, we get
And [non-negative constraint]
He want to find out the maximum distance travelled, here total distance,
Now, we have to maximize the distance, i.e., maximize
So, to maximize distance we have to maximize, ,$ subject to
When we convert it into equation we get
The region that is represented by 2x+3y≤120:
The line that is 2x+3y=120 further meets the coordinate axes (60,0) and (0,40) respectively and then when we will join these points we obtain the line 2x+3y=120. It is clear that (0,0) justifies the inequation 2x+3y≤120. So the region that contain the origin represents the solution set of the inequation 2x+3y≤120
The region represented by 8x+5y≤400:
We can see that the line 8x+5y=400 meets the coordinate axes (50,0) and (0,80) respectively. When we join these points we obtain the line 8x+5y=400. Therefore, it is clear that (0,0) satisfies the inequation 8x+5y≤400. So the region that contain the origin represents the solution set of the inequation 8x+5y≤400
The first quadrant of the region represented is x≥0 and y≥0. The graph is as follows:
The shaded region OBCD is the feasible region is bounded, and maximum value will occur at a corner point of the feasible region.
Corner Points are
When we substitute the values in Z, we get the following answer:
So from the above table the maximum value of Z is at point
Hence, the maximum distance the man can travel is or 54.3 km
Question:21
Answer:
It is given that:
And it is also subject to constraints that is given below:
We have to maximize Z, we are subject to the constraints above.
We need to convert the inequalities into equation to get the following equation:
The region that represents is explained below:
The line meets the coordinate axes (8,0) and (0,2) respectively. We will join these points to obtain the line . It is clear that (0,0) satisfies the inequation . So, the region containing the origin represents the solution set of the inequation
The region that represents :
The line that is then meets the coordinate axes respectively to get the answer. When we join the points we obtain the line . It is clear that (0,0) satisfies the inequation . So, the region containing the origin represents the solution set of the inequation.
The region that represents :
The line meets the coordinate axes that is meets (3,0) and (0,9) respectively. After joining the lines, we get and then it is clear that (0,0) satisfies the inequation. The region that contains the origin is represented by the solution set of .
The graph for the same is given below and also the final answer:
Question:22
Answer:
Let us say that the number of bikes per week of model X and Y are x and y respectively.
Assuming that model X takes 6 man-hours.
So, time taken by x bikes of model X = 6x hours.
Assuming that model Y takes 10 man-hours.
So, time taken by y bikes of model X = 10y hours.
So, the total man-hour that is available per week = 450
So, 6x + 10y ≤ 450
3x + 5y ≤ 225
The handling and the marketing cost of model X and Y is Rs 2000 and Rs 1000 per unit respectively.
So, total handling and marketing cost of x units of model X and y units of model y is 2000x + 1000y
The maximum amount that is available for handling and marketing per week is Rs 80000.
So,
Profits per unit for Models X and Y are Rs 1000 and Rs 500, Respectively.
Let total profit = Z
So,
Also, as units will be positive numbers so x, y ≥ 0
So, we have,
With constraints,
In order to maximize Z, that is subject to constraints.
We need to convert it into equation:
The graph for the same is given below:
ABCD being the feasible region.
The Value of Z as well as the final answer is given below.
The Value of Z at corner points A,B,C and D :
So, value of Z is maximum on-line BC, the maximum value is 40000 . So manufacturer must produce 25 number of models X and 30 number of model Y.
Question:23
The person needs at least 18 milligrams of iron, 21 milligrams of calcium and 16 milligrams of vitamins. The price of each tablet of X and Y is Rs 2 and Re 1 respectively. How many tablets of each should the person take in order to satisfy the above requirement at the minimum cost?
Answer:
Let us say that the number of tablet X be x and the number of tablet Y be y.
Iron content in X and Y tablets is 6 mg and 2 mg respectively.
Total iron content from x and y tablets = 6x + 2y
Minimum of 18 mg of iron is required. So, we have
Similarly, calcium content in X and Y tablets is 3 mg each respectively.
So, total calcium content from x and y tablets = 3x + 3y
Minimum of 21 mg of calcium is required. So, we have
Also, vitamin content in X and Y tablet is 2 mg and 4 mg respectively.
So, total vitamin content from x and y tablets = 2x + 4y
Minimum of 16 mg of vitamin is required. So, we have
Also, as number of tablets should be non-negative so, we have,
x, y ≥ 0
Cost of each tablet of X and Y is Rs 2 and Re 1 respectively.
Let total cost = Z
So, Z = 2x + y
Finally, we have,
Constraints,
We need to minimize Z, subject to the given constraints.
Now let us convert the given inequalities into equation.
We obtain the following equation
The region that is representing 3x + y ≥ 9 is the line 3x + y = 9 meets the coordinate axes (3,0) and (0,9) respectively. Once the points are joined, the lines are obtained 3x + y = 9. It does not satisfy the inequation and so the region that contains the origin then represents the solution set of the inequation 3x + y ≥ 9.
The region that is representing x + y ≥ 7 is the line x + y = 7 meets the coordinate axes (7,0) and (0,7) respectively. Once the points are joined, the lines are obtained v It does not satisfy the inequation and so the region that contains the origin then represents the solution set of the inequation x + y ≥ 7.
The region representing x + 2y ≥ 8 is the line x + 2y = 8 meets the coordinate axes (8,0) and (0,4) respectively. We will join these points to obtain the line x + 2y = 8. It is clear that (0,0) does not satisfy the inequation x + 2y ≥ 8. So, the region not containing the origin represents the solution set of the inequation x + 2y ≥ 8.
The regions that represent x≥0 and y≥0 is first quadrant, since every point in the first quadrant satisfies these inequations.
Given below is the graph:
The region towards the right of ABCD is the feasible region. It is unbounded in this case.
Value of Z at corner points A,B,C and D :
Now, we check if to check if resulting open half has any point common with feasible region.
The region represented by :
The line meets the coordinate axes (4,0) and (0,8) respectively. We will join these points to obtain the line . It is clear that (0,0) satisfies the inequation . So, the region not containing the origin represents the solution set of the inequation .
Clearly, intersects feasible region only at B.
So, does not have any point inside feasible region.
So, value of Z is minimum at B(1,6), the minimum value is 8 .
So, number of tablets that should be taken of type X and Y is 1,6 Respectively.
Question:24
Answer:
Taking into consideration that Let number of days for which factory I operate be x and number of days for which factory II operates be y.
Number of calculators made by factory I and II of model A are 50 and 40 respectively.
Minimum number of calculators of model A required = 6400
So, 50x + 40y ≥ 6400
⇒ 5x + 4y ≥ 640
Number of calculators made by factory I and II of model B are 50 and 20 respectively.
Minimum number of calculators of model B required = 4000
So, 50x + 20y ≥ 4000
⇒ 5x + 2y ≥ 400
Number of calculators made by factory I and II of model C are 30 and 40 respectively.
Minimum number of calculators of model C requires = 4800
So,
Operating costs is Rs 12000 and Rs 15000 each day to operate factory I and II respectively.
Let Z be total operating cost so we have Z = 12000x + 15000y
Also, number of days are non-negative so, x, y ≥ 0
So, we have,
Constraints,
We need to minimize Z, subject to the given constraints.
Now let us convert the given inequalities into equation.
We obtain the following equation
The region that represents the 5x + 4y ≥ 640.
The line 5x + 4y = 640 meets the coordinate axes (128,0) and (0,160) respectively to get the final outcome. When we join these points to obtain the line 5x + 4y = 640. It is then clear that (0,0) does not satisfy the inequation 5x + 4y ≥ 640. So, the region not containing the origin represents the solution set of the inequation 5x + 4y ≥ 640.
The region that represents the 5x + 2y ≥ 400:
The line 5x + 2y = 400 meets the coordinate axes (80,0) and (0,200) respectively. We will join these points to obtain the line 5x + 2y = 400. It is justified that (0,0) does not satisfy the inequation 5x + 2y ≥ 400. So, the region not containing the origin represents the solution set of the inequation 5x + 2y ≥ 400.
The region represented by 3x + 4y ≥ 480:
The line that 3x + 4y = 480 when meets the coordinate axes (160,0) and (0,120) respectively. We will then try and join these points to obtain the line 3x + 4y = 480. It is clear that (0,0) does not justify the inequation 3x + 4y ≥ 480. So, the region not containing the origin represents the solution set of the inequation 3x + 4y ≥ 480.
The graph is:
The region towards the right of ABCD is the feasible region. It is unbounded in this case.
The value of Z at the corner points, is
Now, we plot to check if resulting open half has any point common with feasible region.
The region represented by
The line meets the coordinate axes (155,0) and (0,124) respectively. We will join these points to obtain the line $. It is clear that (0,0) satisfies the inequation . So, the region containing the origin represents the solution set of the inequation .
Clearly, intersects feasible region only at C
So, value of Z is minimum at C(80,60), the minimum value is 1860000 .
So, number of days factory 1 is required to operate is 80 and number of days factory 2 should operate is 60 to minimize the cost.
Question:25
Maximise and Minimise Z = 3x - 4y
subject to
Answer:
We need to maximize and minimize Z, subject to the given constraints.
Now let us convert the given inequalities into equations.
We obtain the following equation
We have constraints,
We need to maximize and minimize Z, subject to the given constraints.
Now let us convert the given inequalities into equations.
We obtain the following equation
The further explanation of the same is given below:
The region represented by x – 2y ≤ 0:
The line x - 2y = 0 meets the coordinate axes at origin and slope of the line is . We will construct a line passing through origin and whose slope is . As point (1,1) satisfies the inequality. So, the side of the line which contains (1,1) is feasible. Hence, the solution set of the inequation x – 2y ≤ 0 is the side which contains (1,1).
The region represented by – 3x + y ≤ 4:
The line – 3x + y = 4 meets the coordinate axes and (0,4) respectively. We will join these points to obtain the line -3x + y = 4. It is clear that (0,0) satisfies the inequation – 3x + y ≤ 4. So, the region containing the origin represents the solution set of the inequation – 3x + y ≤ 4.
The region represented by x – y ≤ 6:
The line x – y = 6 then meets the coordinate axes (6,0) and (0,-6) respectively. We will join these points to obtain the line x – y = 6. It is clear that (0,0) satisfies the inequation x – y ≤ 6. So, the region containing the origin represents the solution set of the inequation x – y ≤ 6.
The graph for the same is given below:
The feasible region is region between line above BC and to the right of y axis as shown.
Feasible region is unbounded.
Corner points are A, B, C
Value of Z at corner points A, B, C and D –
So, maximum value of Z at corner points is 12 at C and minimum is -16 at A.
So, to check if the solution is correct, we plot 3 x-4 y>12 and 3 x-4 y<-16 for maximum and minimum respectively.
The region represented by 3 x-4 y>12
The line that is 3x – 4y = 12 meets the coordinate axes (4,0) and (0,-3) respectively. When we join these points, we get the line 3x – 4y > 12. It is clear that (0,0) does not satisfy the inequation 3x – 4y > 12. So, the region not containing the origin represents the solution set of the inequation 3x – 4y > 12.
The region represented by 3x – 4y <-16:
The line 3x – 4y = -16 meets the coordinate axes and (0,4) respectively. We will join these points to obtain the line 3x – 4y <-16. It is clear that (0,0) does not satisfy the inequation 3x – 4y <-16. So, the region not containing the origin represents the solution set of the inequation 3x – 4y <-16.
We get the following answer:
Clearly, has no point inside feasible region, but passes through the feasible region.
Therefore, Z has no minimum value it has only a maximum value which is 12.
Question:26
Compare the quantity in Column A and Column B.
A. The quantity in column A is greater
B. The quantity in column B is greater
C. The two quantities are equal
D. The relationship cannot be determined on the basis of the information supplied
Answer:
B)
The quantity in column B is greater
Corner points- (0, 0), (0, 40), (20, 40), (60, 20), (60, 0)
A feasible region is bounded.
Value of Z at corner points-
At (0, 0), Z = 0
At (0, 40), Z = 120
At (20, 40), Z = 200
At (60, 20), Z = 300
At (60, 0), Z = 240
Clearly, the maximum value of Z is 300, which is less than 325.
Question:27
The feasible solution for a LPP is shown in Fig. 12.12. Let Z = 3x – 4y be the
objective function. Minimum of Z occurs at
A. (0, 0)
B. (0, 8)
C. (5, 0)
D. (4, 10)
Answer:
B)
Answer
Value of Z = 3x – 4y, at corner points are –
At (0, 0) = 0
At (0, 8) = -32
At (4, 10) = -28
At (6, 8) = -14
At (6, 5) = -2
At (5, 0) = 15
So, clearly minimum value is at (0, 8)
Question:28
Refer to Exercise 27. Maximum of Z occurs at
A. (5, 0)
B. (6, 5)
C. (6, 8)
D. (4, 10)
Answer:
Correct Answer A
Answer
Value of Z = 3x – 4y, at corner points are –
At (0, 0) = 0
At (0, 8) = -32
At (4, 10) = -28
At (6, 8) = -14
At (6, 5) = -2
At (5, 0) = 15
So, clearly maximum value is at (5, 0)
Question:29
Refer to Exercise 27. (Maximum value of Z + Minimum value of Z) is equal to
A. 13
B. 1
C. – 13
D. – 17
Answer:
Correct Answer D)
Answer:
Value of Z = 3x – 4y, at corner points are –
At (0, 0) = 0
At (0, 8) = -32
At (4, 10) = -28
At (6, 8) = -14
At (6, 5) = -2
At (5, 0) = 15
So, clearly maximum value is at (5, 0)
Maximum value = 15,
Minimum value = -32
So, maximum + minimum = 15 -32
= -17
Question:30
The feasible region for an LPP is shown in the Fig. 12.13. Let F = 3x – 4y be the objective function. Maximum value of F is.
A. 0
B. 8
C. 12
D. – 18
Answer:
Correct Answer C)
Answer:
F = 3x – 4y
Corner points are (0, 0), (0, 4), (12, 6)
Value of F at corner points –
At (0, 0), F = 0
At (0, 4), F = -16
At (12, 6), F = 12
Clearly, the maximum value of F = 12.
Question:31
Refer to Exercise 30. Minimum value of F is
A. 0
B. – 16
C. 12
D. does not exist
Answer:
Correct Answer B)
Answer:
F = 3x – 4y
Corner points are (0, 0), (0, 4), (12, 6)
Value of F at corner points –
At (0, 0), F = 0
At (0, 4), F = -16
At (12, 6), F = 12
Clearly, the minimum value of F = – 16.
Question:32
Corner points of the feasible region for an LPP are (0, 2), (3, 0), (6, 0), (6, 8) and (0, 5). Let F = 4x + 6y be the objective function.
The Minimum value of F occurs at
A. (0, 2) only
B. (3, 0) only
C. the midpoint of the line segment joining the points (0, 2) and (3, 0) only
D. any point on the line segment joining the points (0, 2) and (3, 0).
Answer:
Correct Answer D)
Answer:
F = 4x + 6y
Corner points - (0, 2), (3, 0), (6, 0), (6, 8) and (0, 5).
Value of F at corner points –
At (0, 2), F = 12
At (3, 0), F = 12
At (6, 0), F = 24
At (6, 8), F = 72
At (0, 5), F = 30
Feasible region –
As, feasible region to be bounded so it is a closed polygon.
So, minimum values of F = 12 are at (3, 0) and (0, 2).
Therefore, the minimum value of F occurs at any point on the line segment joining the points (0, 2) and (3, 0).
Question:33
Refer to Exercise 32, Maximum of F – Minimum of F =
A. 60
B. 48
C. 42
D. 18
Answer:
Correct Answer A)
Answer:
F = 4x + 6y
Corner points - (0, 2), (3, 0), (6, 0), (6, 8) and (0, 5).
Value of F at corner points –
At (0, 2), F = 12
At (3, 0), F = 12
At (6, 0), F = 24
At (6, 8), F = 72
At (0, 5), F = 30
Feasible region –
Considering, feasible region to be bounded so it is a closed polygon.
Minimum value of F = 12
Maximum value of F = 72
So, Maximum of F – Minimum of F = 60.
Question:34
Corner points of the feasible region determined by the system of linear constraints are (0, 3), (1, 1) and (3, 0). Let , where p, q > 0. Condition on p and q so that the minimum of Z occurs at (3, 0) and (1, 1) is
A. p = 2q
B. p = q/2
C. p = 3q
D. p = q
Answer:
Given,
Given, minimum occurs at (3, 0) and (1, 1).
For a minimum to occur at two points the value of Z at both points should be the same.
So, value of Z at (3, 0) = value of Z at (1, 1)
⇒ 3p = p + q
⇒ 2p = q
So, option B is correct.
Question:35
Answer:
In a LPP, the linear inequalities or restrictions on the variables are called linear constraints.
Question:36
Fill in the blanks in each of the Exercise.
In a LPP, the objective function is always _________
Answer:
In a LPP, the objective function is always linear.
Question:37
Answer:
If the feasible region for a LPP is unbounded, then the optimal value of the objective function Z = ax + by may or may not exist.
Question:38
Answer:
In a LPP if the objective function Z = ax + by has the same maximum value on two corner points of the feasible region, then every point on the line segment joining these two points give the same maximum value
Question:39
Answer:
A feasible region of a system of linear inequalities is said to be bounded if it can be enclosed within a circle.
Question:40
Answer:
A corner point of a feasible region is a point in the region which is the intersection of two boundary lines.
Question:41
Answer:
The feasible region for an LPP is always a convex polygon.
Question:42
Answer:
True
If the feasible region is unbounded then we may or may not have a maximum or minimum of objective function, but if we have a maximum or a minimum value then it must be at one of the corner points only.
Question:43
Answer:
False.
Maximum value or minimum value can occur at more than one point. In such all the points lie on a line segment and are part of the boundary of the feasible region.
Question:44
Answer:
False.
Minimum value of objective function can also be negative if the coefficient of x or y is negative. So, it is not necessary that the minimum value of objective function will be zero.
Question:45
Answer:
False.
In a LPP, the maximum value of the objective function may or may not be finite. It depends on the feasible region. If a feasible region is unbounded then we can also have infinite maximum value of objective function.
Class 12 Maths NCERT exemplar solutions chapter 12 introduces us to the definition of Linear programming as a mathematical modelling technique in which a function is deemed maximum or minimum when subjected to several constraints. The solution of a linear programming problem targets finding the optimal value of a linear expression.
While some linear programming are quick and does not require a pen and a paper, quite often, the calculations and variables become too complicated but don't worry; NCERT exemplar solutions for Class 12 Maths chapter 12 provided on this page would always give you a quick head-start and aid you in doing well in your 12 board exams and competitive exams.
The topics and subtopics are as follows:
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Chapter 1 | |
Chapter 2 | |
Chapter 3 | |
Chapter 4 | |
Chapter 5 | |
Chapter 6 | |
Chapter 7 | |
Chapter 8 | |
Chapter 9 | |
Chapter 10 | |
Chapter 11 | |
Chapter 12 | Linear Programming |
Chapter 13 |
These days linear programming is helpful in almost every field and industry from finance to engineering to medicine. Learning this chapter will help in getting a better understanding of mathematical modeling.
Yes, these NCERT exemplar Class 12 Maths solutions chapter 12 are helpful in the preparation of all types of engineering entrance exams like JEE Main and others.
These solutions are prepared by our highly experienced experts and teachers, who have years of experience and knowledge regarding NCERT and CBSE pattern and requirement.
Yes, the NCERT exemplar solutions for Class 12 Maths chapter 12 given here are exhaustive with each step mentioned in complete detail. The solutions are also as per the CBSE guidelines and pattern.
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Hello there! Thanks for reaching out to us at Careers360.
Ah, you're looking for CBSE quarterly question papers for mathematics, right? Those can be super helpful for exam prep.
Unfortunately, CBSE doesn't officially release quarterly papers - they mainly put out sample papers and previous years' board exam papers. But don't worry, there are still some good options to help you practice!
Have you checked out the CBSE sample papers on their official website? Those are usually pretty close to the actual exam format. You could also look into previous years' board exam papers - they're great for getting a feel for the types of questions that might come up.
If you're after more practice material, some textbook publishers release their own mock papers which can be useful too.
Let me know if you need any other tips for your math prep. Good luck with your studies!
It's understandable to feel disheartened after facing a compartment exam, especially when you've invested significant effort. However, it's important to remember that setbacks are a part of life, and they can be opportunities for growth.
Possible steps:
Re-evaluate Your Study Strategies:
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Hi,
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hello mahima,
If you have uploaded screenshot of your 12th board result taken from CBSE official website,there won,t be a problem with that.If the screenshot that you have uploaded is clear and legible. It should display your name, roll number, marks obtained, and any other relevant details in a readable forma.ALSO, the screenshot clearly show it is from the official CBSE results portal.
hope this helps.
Hello Akash,
If you are looking for important questions of class 12th then I would like to suggest you to go with previous year questions of that particular board. You can go with last 5-10 years of PYQs so and after going through all the questions you will have a clear idea about the type and level of questions that are being asked and it will help you to boost your class 12th board preparation.
You can get the Previous Year Questions (PYQs) on the official website of the respective board.
I hope this answer helps you. If you have more queries then feel free to share your questions with us we will be happy to assist you.
Thank you and wishing you all the best for your bright future.
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