JEE Questions for Maths Linear Programming Quiz 1 - MCQExams.com

The maximum value of z = 9x + 13y, subject to constraints 2x + 3y ≤ 18, 2x + y ≤ 10, x ≥ 0 and y ≥ 0 is
  • 130
  • 81
  • 79
  • 99
Variables of the objective function of the linear programming problem are
  • zero
  • zero or positive
  • negative
  • zero or negative
The area of the feasible region for the following constraints 3y + x ≥ 3 , x ≥ 0 and y ≥ 0 will be
  • bounded
  • unbounded
  • convex
  • concave
Maximum value of z =12x + 3y, subject to constraints x ≥ 0, y ≥ 0, x + y ≤ 5 and 3x + y ≤ 9 is
  • 15
  • 36
  • 60
  • 40
The region represented by the inequation system x , y ≥ 0, y ≤ 6 , x + y ≤ 3 is
  • unbounded in first quadrant
  • unbounded in first and second quadrants
  • bounded in first quadrant
  • None of the above
Which of the term is not used in a linear programming problem?
  • Optimal solution
  • Feasible solution
  • Concave region
  • Objective function
The maximum value of z = 4x + 2y subject to constraints 2x + 3y ≤ 18 , x + y ≥ 10 and x , y ≥ 0 is
  • 20
  • 36
  • 40
  • None of these
The maximum value of z is where, z = 4x + 2y subject to constraints 4x + 2y ≥ 46 , x + 3y ≤ 24 and x, y ≥ 0, is
  • 46
  • 96
  • 52
  • None of these
Maximum value of z = 3x + 4y subject to constraints x - y ≥ -1, -x + y ≤ 0 and x , y ≥ 0, is given by
  • 1
  • 4
  • 6
  • no feasible region
A furniture dealer deals in only two items namely tables and chairs. He has Rs 5000 to invest and space to store atmost 60 pieces. A table cost him Rs 250 and a chair Rs 60. He can sell a table at a profit of Rs 15. Assume that, he can sell all the items that he produced. The number of constraints in the problem are
  • 2
  • 3
  • 4
  • 5
If x + y ≤ 2 ; x ≥ 0, y ≥ 0 is the point at which maximum value of 3x + 2y attained will be
  • ( 0, 2 )
  • ( 0, 0 )
  • ( 2, 0 )

  • Maths-Linear Programming-37995.png
Which of the following sets are not convex?
  • {(x , y) : 8x2 + 6y2 ≤ 24}
  • {(x , y) : 6 ≤ x2 + y2 ≤ 36}
  • {(x , y): y ≥ 3, y ≥ 30}
  • {(x , y): x2 ≤ y
Consider the linear programming problem
Maximise z = 4x + y
Subject to constraints x + y ≤ 50, x + y ≥ 100,
and x, y ≥ 0
Then, maximum value of z is
  • 0
  • 50
  • 100
  • does not exist
The point which provides the solution of the linear programming problem, maximise z = 45x + 55y
Subject to constraints x, y ≥ 0, 6x + 4y ≤ 120 and 3x + 10y ≤ 180 is
  • ( 15 , 10 )
  • ( 10 , 15 )
  • ( 0 , 18 )
  • ( 20 , 0 )
The linear programming problem
Maximise z = x1 + x2
Subject to constraints x1 + 2x2 ≤ 2000, x1 + x2 ≤ 1500, x2 ≤ 600 and x1 ≥ 0 has
  • no feasible solution
  • unique optimal solution
  • a finite number of optimal solutions
  • infinite number of optimal solutions
The optimal value of the objective function is attained at the point is
  • given by intersection of inequations with axes only
  • given by intersection of inequations with X-axis only
  • given by corner points of the feasible region
  • None of the above
The maximum value of z = 10x + 6y, subject to constraints x ≥ 0, y ≥ 0, x + y ≤ 12, 2x + y ≤ 20 is
  • 72
  • 80
  • 104
  • 110
A vertex of a feasible region by the linear constraints 3x + 4y ≤ 18, 2x + 3y ≥ 3 and x, y ≥ 0 is
  • (0, 2)
  • (4.8, 0)
  • (0, 3)
  • None of these
For an LPP, minimise z = 2x + y subject to constraints 5x + 10y ≤ 50 , x + y ≥ 1, y ≤ 4 and x,y ≥ 0, then z is equal to
  • 0
  • 1
  • 2
  • 12
For the LPP, minimise z = x1 + x2 such that inequalities 5x1 + 10x2 ≥ 0, x1 + x2 ≤ 1, x2 ≤ 4 and x1 , x2 ≥ 0
  • There is a bounded solution
  • There is no solution
  • There are infinite solutions
  • None of the above
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