Linear Programming is crucial for both board and competitive exams because it provides a systematic method to optimize a quantity under multiple linear constraints. Problems based on feasible regions, corner points (vertices), and conditions for unique vs infinite optimal solutions frequently appear in CBSE and JEE/NEET-style questions, making strong concept clarity essential.
15
Minutes
10
Questions
1 / -0
Marking
Q1. Maximise subject to
Find the maximum value of .
Q2. For which value of does the maximum value of subject to
occur at both points and simultaneously?
Q3. A factory makes two products P and Q. Each unit of P requires hours on machine A and hour on machine B. Each unit of Q requires hour on machine A and hours on machine B. Machine A is available for hours and machine B for hours. Profit per unit is Rs. for P and Rs. for Q. Let denote units of P and Q produced. Maximise subject to
The maximum profit (in rupees) is:
Q4. Maximise subject to
The set of optimal solutions forms a line segment. The length of that segment is:
Q5. Let and consider maximise subject to
The point is a vertex of the feasible region. For which range of (in terms of ) will be the unique optimal solution?
Q6. For the feasible region defined by , the maximum value of is:
Q7. Consider the linear programming problem subject to . Which of the following is true?
The unique maximum occurs at .
The unique maximum occurs at .
is unbounded above.
Every point on the line segment joining and is optimal (infinitely many optimal solutions).
Q8. Find the minimum value of subject to .
Minimum at .
Minimum at .
Minimum at .
No minimum (unbounded below).
Q9. For which value(s) of the parameter does the linear program subject to have infinitely many optimal solutions?
No real value of
Q10. For the problem subject to , if an additional constraint is imposed, the new optimal solution is:
The feasible region becomes empty (no feasible solution)