Linear Programmig Problem MCQ Quiz in বাংলা - Objective Question with Answer for Linear Programmig Problem - বিনামূল্যে ডাউনলোড করুন [PDF]

Last updated on Apr 4, 2025

পাওয়া Linear Programmig Problem उत्तरे आणि तपशीलवार उपायांसह एकाधिक निवड प्रश्न (MCQ क्विझ). এই বিনামূল্যে ডাউনলোড করুন Linear Programmig Problem MCQ কুইজ পিডিএফ এবং আপনার আসন্ন পরীক্ষার জন্য প্রস্তুত করুন যেমন ব্যাঙ্কিং, এসএসসি, রেলওয়ে, ইউপিএসসি, রাজ্য পিএসসি।

Latest Linear Programmig Problem MCQ Objective Questions

Top Linear Programmig Problem MCQ Objective Questions

Linear Programmig Problem Question 1:

Consider the inequations 2x + y > 3, x + 2y > 6 and x, y > 0. Which one of the following points lies in the common region?

  1. (2, 1.5)
  2. (2, 2)
  3. (3, 1)
  4. (3, 5)

Answer (Detailed Solution Below)

Option 4 : (3, 5)

Linear Programmig Problem Question 1 Detailed Solution

Calculation:

Converting the inequations to equations, we obtain:

2x + y = 3, x + 2y = 6, x = 0, y = 0.

For 2x + y = 3 

  • Putting x = 0, 0 + y = 3 ⇒ y = 3
  • Putting y = 0, 2x + 0 = 3 ⇒ x = \(\frac{3}{2}\)
  • This line meets the x-axis at \(\left ( \frac{3}{2},0 \right )\) and the y-axis at (0, 3). Draw a line through these points.
  • We see that the origin (0, 0) does not satisfy the inequation 2x + y > 3
  • Therefore, the region that does not contain the origin is the solution of the inequality 2x + y > 3

For x + 2y = 6

  • Putting x = 0, 0 + 2y = 6 ⇒ y = 3
  • Putting y = 0, x + 0 = 6 ⇒ x = 6
  • This line meets the x-axis at (6, 0) and the y-axis at (0, 3). Draw a line through these points.
  • We see that the origin (0, 0) does not satisfy the inequation x + 2y > 6
  • Therefore, the region that does not contain the origin is the solution of the inequality x + 2y > 6

F3 Defence Savita 10-11-22 D2

The solution to the inequalities is the intersection of the 2x + y > 3, x + 2y > 6 and x, y > 0. Thus, the shaded region represents the solution set of the given set of inequalities.

Now solving 2x + y = 3 and x + 2y = 6, we get the point P(0, 3).

Now, Putting (3, 5) in 2x + y > 3,

2(3) + 5 > 3 ⇒ 11 > 3 which is true.

Again, putting (3, 5) in x + 2y > 6,

3 + 2(5) > 6 ⇒ 13 > 6 which is true.

∴ (3, 5) lies in the common region.

So, the correct option is (4)

Linear Programmig Problem Question 2:

Consider an objective function Z(x, y) = 11x + 7y

And the constraints:

2x + y ≤ 6

x ≤ 2

x ≥ 0, y ≥ 0

The maximum value of the objective function is.....

  1. 42
  2. 54
  3. 18
  4. 36

Answer (Detailed Solution Below)

Option 1 : 42

Linear Programmig Problem Question 2 Detailed Solution

Solution:

Given that, Z = 11x + 7y and the constraints 2x + y ≤ 6, x ≤ 2, x ≥ 0, y ≥ 0

Let 2x + y = 6

x 0 3
y 6 0
F3 Defence Savita 10-11-22 D5

Now, plotting all the constrain equations we see that the shaded area OABC is the feasible region determined by the constraints.

The feasible region is bounded. So, the maximum value will occur at a corner point of the feasible region.

Corner points are (0, 0), (2, 0), (2, 2) and (0, 6).

On evaluating the value of Z, we get

Corner Points

Value of Z

O(0, 0)

0

A(2, 0)

22

B(2, 2)

36

C(0, 6)

42

From the above table, it's seen that the maximum value of Z is 42.

Therefore, the maximum value of Z is 42 at (0, 6).

∴ The correct option is (1)

Linear Programmig Problem Question 3:

Corner points of the feasible region determined by the system of linear constrains are (0, 3), (1, 1) and (3, 0). Let Z = px + qy, where p, q > 0. Condition on p and q so that the minimum of Z occurs at (3, 0) and (1, 1) is?

  1. p = 2q
  2. p = q/2
  3. p = 3q
  4. p = q

Answer (Detailed Solution Below)

Option 2 : p = q/2

Linear Programmig Problem Question 3 Detailed Solution

CONCEPT:

  • At the corner point of the feasible reason, we have to check the value of the objective function to get the maximum value.

CALCULATION:

Given:

Corner points

Corresponding value of

Z = px + qy; p, q > 0

(0, 3) 3q
(1, 1) p + q
(3, 0) 3p


So, the condition of p and q, so that the minimum of Z occurs at (3, 0) and (1, 1) can be extracted by equating the minimum values of Z for (3, 0) and (1, 1).

⇒ p + q = 3p

⇒ 2p = q

∴ \(\rm p=\frac{q}{2}\)

  • So, the correct answer will be option 2.

Linear Programmig Problem Question 4:

Corner points of the feasible region determined by the system of linear constraints are (0, 3), (1, 1), and (3, 0). Let Z = px + qy, where p, q > 0.

Condition on p and q so that the minimum of Z occurs at (3, 0) and (1, 1) is

  1. p = 2q
  2. p = \(\rm\frac{q}{2}\)
  3. p = 3q
  4. p = q

Answer (Detailed Solution Below)

Option 2 : p = \(\rm\frac{q}{2}\)

Linear Programmig Problem Question 4 Detailed Solution

Explanation:

 Z = px + qy, where p, q > 0

Corner points of the feasible region determined by the system of linear constraints are (0, 3), (1, 1), and (3, 0)

Let z0​ be the minimum value of z in the feasible region.

Since the minimum occurs at both (3, 0) and (1, 1).

The value z0​ is attained at both (3, 0) and (1, 1).

z0​ = p × 3 + q × 0     ---- (1)

z​= p × 1 + q × ​1     ---- (2)

From Equations (1) and (2) we get 

⟹ p × 3 + q × 0 = × 1 + q × ​1 

⟹ 3 p = p + q

⟹ 2 p = q

⟹ p = q/2

The Correct Option is (2).

Linear Programmig Problem Question 5:

Consider an objective function Z(x, y) = 5x + 3y

And the constraints:

3x + 5y ≤ 15

5x + 2y ≤ 10

x ≥ 0, y ≥ 0

The maximum value of Z occurs at 

  1. \(\left ( \frac{13}{19},\frac{55}{19} \right )\)
  2. \(\left ( \frac{3}{19},\frac{5}{19} \right )\)
  3. \(\left ( \frac{20}{19},\frac{45}{19} \right )\)
  4. \(\left ( \frac{34}{19},\frac{56}{19} \right )\)

Answer (Detailed Solution Below)

Option 3 : \(\left ( \frac{20}{19},\frac{45}{19} \right )\)

Linear Programmig Problem Question 5 Detailed Solution

Solution:

Given that, Z = 5x + 3y and the constraints 3x + 5y ≤ 15, 5x + 2y ≤ 10, x ≥ 0, y ≥ 0

Taking 3x + 5y = 15, we have

x 0 5
y 3 0

And, taking 5x + 2y = 10, we have

x 0 2
y 5 0

F3 Defence Savita 10-11-22 D3

Now, plotting all the constrain equations we see that the shaded area OABC is the feasible region determined by the constraints.

The feasible region is bounded. So, the maximum value will occur at a corner point of the feasible region.

Corner points are (0, 0), (2, 0), (0, 3) and \(\left ( \frac{20}{19},\frac{45}{19} \right )\)

On evaluating the value of Z, we get

Corner Points

Value of Z

O(0, 0)

0

A(2, 0)

10

B(0, 3)

9

C\(\left ( \frac{20}{19},\frac{45}{19} \right )\)

\(\frac{235}{19}\)

From the above table, it's seen that the maximum value of Z is \(\frac{235}{19}\).

Therefore, the maximum value of the function Z is \(\frac{235}{19}\) at \(\left ( \frac{20}{19},\frac{45}{19} \right )\).

∴ The correct option is (3)

Linear Programmig Problem Question 6:

Consider a product manufacturing company that makes products A and B. The company uses electricity and diesel as energy sources. For the production of A, 1 unit (not kWh) of electricity and 3 units of diesel are required and for B, 1 unit of electricity and 2 units of diesel are required. The company's captive power plant supplies 5 units of electricity and 12 units of diesel.

Product

Electricity required (units)

Diesel required (units)

A

1

3

B

1

2

On the sale of A and B, the company makes a profit of Rs 60 and 50 respectively. Which of the following is representing the objective function subject to the constraints? Take x units of A and y be the units of B being sold. 

  1. Max Z = 60x + 50y, x + y ≤ 5, 3x + 2y ≤ 12

  2. Max Z = 50x + 60y, x + y ≤ 5, 3x + 2y ≤ 12

  3. Min Z = 60x + 50y, x + 2y ≤ 5, 3x + y ≤ 12

  4. Min Z = 60x + 50y, x + y ≤ 5, 3x + 2y ≤ 12

Answer (Detailed Solution Below)

Option 1 :

Max Z = 60x + 50y, x + y ≤ 5, 3x + 2y ≤ 12

Linear Programmig Problem Question 6 Detailed Solution

Concept: 

There are three main components of linear programming:

  • Decision Variables: These variables are the activities that share the available resources while also competing with one another. In other words, these are interrelated in terms of resource utilization and need to be solved simultaneously. They are assumed to be non-negative and continuous.  
  • The Objective Function: Each linear programming problem is aimed to have an objective to be measured in quantitative terms such as profits, sales, cost, time, or some other parameter, etc which needs to be maximized or minimized. The objective function will vary depending upon the business requirements or other factors.
  • Constraints: These represent real-life limitations such as money, time, labor or other restrictions and the objective function needs to be maximized or minimized while satisfying the constraints. They are represented as linear equations or inequations in terms of the decision variables.

For example, suppose x and y are the decision variables. The objective function will be given by:

Z = ax + by ….(1)

Where a and b are constants and Z is the function to be maximized or minimized. There will be conditions x ≥ 0, and y ≥ 0, which indicates the non-negative constraints on the decision variable.

The equation looks very simple since there are various assumptions involved while forming a linear programming example. These are mentioned below:

  • Parameters such as resources available, profit contribution of unit decision variable and resource used by unit decision variable needs to be known.
  • Decision variables are continuous. Hence the outputs can be an integer or a fraction.
  • The contribution of each decision variable in the objective function is directly proportional to the objective function.

Calculation:

Given:

x, y: Number of units of A and B being sold respectively.

It is very beneficial if the information is converted to a tabular form to make the data visualization much easier. As per the above info, the table is formed below:

Product

Electricity required (units)

Diesel required (units)

Profit made by selling

A

1

3

Rs 60

B

1

2

Rs 50

Total resource available

5

12

 

 

  • Since x and y cannot be negative, x ≥ 0      …(2) and y ≥ 0      ….(3)
  • One unit of A takes 1 unit of electricity and 3 units of diesel.   
  • Similarly, one unit of B takes 1 unit of electricity and 2 units of diesel.   

x + y ≤ 5       ….(4) and 3x + 2y ≤ 12       ….(5)

  • The objective function will be the profit obtained by selling x units of A and y units of B.

⇒ Z = 60x + 50y ….(6)

  • Hence, the problem is represented mathematically by (2), (3), (4), (5), and (6).
  • So, the correct answer is option 1.

Linear Programmig Problem Question 7:

Consider the following Linear Programming problem:

Maximise Z = 40x1 + 50x2

subject to the constraints

x1 + 2x2 ≤ 40,

4x1 + 3x2 ≤ 120,

x1, x2 ≥ 0.

Then the optimal solution is:

  1. Z = 1600 for x1 = 30, x2 = 8
  2. Z = 1360 for x1 = 24, x2​ = 8
  3. Z = 1460 for x1 = 24, x2​ = 10
  4. Z = 1360 for x1 = 19, x2​ = 12

Answer (Detailed Solution Below)

Option 2 : Z = 1360 for x1 = 24, x2​ = 8

Linear Programmig Problem Question 7 Detailed Solution

Concept

Convert the inequality constraints into equations and find the common points of the bounded region

Calculation

Given LPP

Maximise Z = 40x1 + 50x2

subject to the constraints

x1 + 2x2 ≤ 40,

4x1 + 3x2 ≤ 120,

x1, x2 ≥ 0.

Convert the inequality constraints into equations, we have

x1 + 2x2 = 40,                ..........(1)

4x1 + 3x2 = 120,            ..........(2)

Plotting the Constraints:

1 For x1 + 2x2 = 40

If x1 = 0 , then 2x2 = 40 ⇒ x2 = 20 

If x2 = 0 , then x1 = 40 

So, the line passes through points (0, 20) and (40, 0).

For 4x1 + 3x2 = 120:

If x1 = 0 , then 3x2 = 120   x2 = 40 

If x2 = 0, then 4x1 = 120   x1 = 30 

So, the line passes through points (0, 40) and (30, 0).

Finding Intersection Points:" id="MathJax-Element-110-Frame" role="presentation" style="text-align: center; position: relative;" tabindex="0">

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" id="MathJax-Element-110-Frame" role="presentation" style="text-align: center; position: relative;" tabindex="0"> {x1+2x2=40 4x1+3x2=120" id="MathJax-Element-2-Frame" role="presentation" style="text-align: center; position: relative;" tabindex="0">" id="MathJax-Element-32-Frame" role="presentation" style="text-align: center; position: relative;" tabindex="0"> {x1+2x2=40 4x1+3x2=120" id="MathJax-Element-2-Frame" role="presentation" style="text-align: center; position: relative;" tabindex="0"> Multiply (1) by 4 

⇒ \( 4(x_1 + 2x_2) = 4 \cdot 40 \Rightarrow 4x_1 + 8x_2 = 160 \)

Now subtract the (2) from this result:

 \((4x_1 + 8x_2) - (4x_1 + 3x_2) = 160 - 120\) 

Simplifying:

⇒ \( 5x_2 = 40 \Rightarrow x_2 = 8 \)

Substitute (x2 = 8) back into the first equation:

⇒ \( x_1 + 2(8) = 40 \Rightarrow x_1 + 16 = 40 \Rightarrow x_1 = 24\) 

Therefore, the intersection point is (24, 8).

Vertices of the Feasible Region:

The vertices of the feasible region are:

(0, 0) (intersection of x1 = 0  and x2 = 0 )

(0, 20) (intersection of x1 = 0 and x1 + 2x2 = 40)

(30, 0) (intersection of x2 = 0 and 4x1 + 3x2 = 120

(24, 8) (intersection of x1 + 2x2 = 40 and 4x1 + 3x2 = 120

Evaluate Objective Function ( Z ) at Each Vertex:

At (0, 0) ⇒ Z = 40(0) + 50(0) = 0 

At (0, 20) ⇒ Z = 40(0) + 50(20) = 1000 

At (30, 0) ⇒ Z = 40(30) + 50(0) = 1200 

At (24, 8) ⇒ Z = 40(24) + 50(8) = 960 + 400 = 1360 

Therefore, the optimal solution is at (24, 8) with the maximum value (Z = 1360).

Z = 1360 for x1 = 24, x2​ = 8

Linear Programmig Problem Question 8:

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.

Maximum of F – Minimum of F =

  1. 60
  2. 48
  3. 42
  4. 18

Answer (Detailed Solution Below)

Option 1 : 60

Linear Programmig Problem Question 8 Detailed Solution

Explanation:

Corner points of the feasible region for an LPP are (0, 2), (3, 0), (6,0), (6, 8), and (0,5).
F = 4x + 6y

 

Corner Points Corresponding Value of F = 4x + 6y
(0, 2) 4 × 0 + 6 × 2 = 12 (Minimum)
(3, 0) 4 × 3 + 6 × 0 = 12 (Minimum)
(6,0) 4 × 6 + 6 × 0 = 24
(6, 8) 4 × 6 + 6 × 8 = 72 (Maximum)
(0,5) 4 × 0 + 6 × 5 = 30
 

Maximum of F – Minimum of F = 72 - 12 = 60 

The Correct option is (1).

Linear Programmig Problem Question 9:

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

  1. (0, 2) only
  2. (3, 0) only
  3. the mid point of the line sgment joining the points (0, 2) and (3, 0) only
  4. any point on the line segment joining the points (0, 2) and (3, 0).

Answer (Detailed Solution Below)

Option 4 : any point on the line segment joining the points (0, 2) and (3, 0).

Linear Programmig Problem Question 9 Detailed Solution

Explanation:

Corner points of the feasible region for an LPP are (0, 2), (3, 0), (6,0), (6, 8) and (0,5).
F = 4x + 6y

Corner Points

Corresponding Value of

F = 4x + 6y

(0, 2) 4 × 0 + 6 × 2 = 12 (Minimum)
(3, 0) 4 × 3 + 6 × 0 = 12 (Minimum)
(6,0) 4 × 6 + 6 × 0 = 24
(6, 8) 4 × 6 + 6 × 8 = 72 (Maximum)  
(0,5)   4 × 0 + 6 × 5 = 30

 

So the Minimum value of F occurs at any point on the line segment joining the points (0, 2) and (3, 0).

The Correct Option is (4).

Linear Programmig Problem Question 10:

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

  1. (0, 2) only
  2. (3, 0) only
  3. the mid point of the line sgment joining the points (0, 2) and (3, 0) only
  4. any point on the line segment joining the points (0, 2) and (3, 0).

Answer (Detailed Solution Below)

Option 4 : any point on the line segment joining the points (0, 2) and (3, 0).

Linear Programmig Problem Question 10 Detailed Solution

Explanation:

Corner points of the feasible region for an LPP are (0, 2), (3, 0), (6,0), (6, 8) and (0,5).
F = 4x + 6y

Corner Points

Corresponding Value of

F = 4x + 6y

(0, 2) 4 × 0 + 6 × 2 = 12 (Minimum)
(3, 0) 4 × 3 + 6 × 0 = 12 (Minimum)
(6,0) 4 × 6 + 6 × 0 = 24
(6, 8) 4 × 6 + 6 × 8 = 72 (Maximum)  
(0,5)   4 × 0 + 6 × 5 = 30

 

So the Minimum value of F occurs at any point on the line segment joining the points (0, 2) and (3, 0).

The Correct Option is (4).

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