Linear Programming is a core topic in Class 12 Mathematics that trains you to model real-world constraints into mathematical form and to solve optimization problems efficiently. It is frequently asked in CBSE board exams and also forms a base for higher-level reasoning in competitive exams (like JEE/NEET) because it develops strong skills in graphical/vertex methods, feasibility checks, and parameter-based solution analysis.
20
Minutes
15
Questions
1 / -0
Marking
Q1. Maximise subject to
The maximum value of is:
Q2. A factory makes two products A and B. Let and denote the number of units of A and B produced. Each unit of A requires hours on machine I and hour on machine II; each unit of B requires hour on machine I and hours on machine II. Machine I is available for at most hours and machine II for at most hours. Profit per unit of A is ₹ and of B is ₹. The maximum profit (in ₹) is:
₹
₹
₹
₹
Q3. For which values of is the point an optimal solution of the linear program Maximise subject to
?
Q4. Consider the system of inequalities
For which values of the parameter does this system have no feasible solution?
Q5. Consider the linear program Maximise subject to
where are real numbers (no non-negativity restriction). Which of the following is true about the optimal solutions?
The problem has a unique optimal solution at .
The system has no feasible solution.
There are infinitely many optimal solutions; every point with is optimal.
The maximum value of is .
Q6. Maximise subject to
The maximum value of is:
Q7. Consider the linear programming problem: Maximise subject to
The nature of the optimal solution is:
Unique optimal solution at a single vertex
Infinitely many optimal solutions (alternate optima)
No feasible solution
Unbounded (no maximum)
Q8. For which values of does the linear programming problem Maximise subject to
have a unique optimal solution at the vertex ?
Q9. Assertion (A): The feasible region of the linear programming problem given below is unbounded. Reason (R): The linear program has no minimum. Consider: minimise subject to
Which one of the following is correct?
Both (A) and (R) are true and (R) is a correct explanation of (A)
Both (A) and (R) are true but (R) is not a correct explanation of (A)
(A) is true but (R) is false
(A) is false but (R) is true
Q10. Minimise subject to
The minimum value of is:
Q11. Maximise subject to
. The maximum value of is:
Q12. For which values of does the linear programme Maximise subject to
have as an optimal solution (not necessarily unique)?
No real value of makes optimal
Q13. Find the minimum value of subject to
.
No finite minimum
Q14. For what value of does the linear programme Maximise subject to
have infinitely many optimal solutions?
No real value of gives infinitely many optima
Q15. Maximise subject to
. Which constraint is redundant at the optimal solution?
Constraint 3 () is redundant
Constraint 1 () is redundant
Constraint 2 () is redundant
No constraint is redundant