Lesson 3D.5.2
3D.5.2 Graphical solution of two variable problems Quiz: Pearson Edexcel Further Maths, Unit 39
20 questions
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Lesson 3D.5.2, Graphical solution of two variable problems: 20 multiple choice questions for the Pearson Edexcel Further Maths (9FM0), Unit 39: Linear programming, written with Revision Ninja.
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The 20 questions
-
The feasible region in a graphical linear programme is bounded by
- the constraint lines and the non-negativity axes
- the objective line only
- a parabola
- the coordinate axes only
-
The optimal solution of a linear programme occurs at
- the origin always
- the centre of the region
- a vertex (corner point) of the feasible region
- any interior point
-
In the objective line method, the objective line is moved
- rotated about the origin
- parallel to itself across the feasible region
- only through the origin
- perpendicular to the region
-
In the vertex method, for a maximisation, you evaluate the objective at each vertex and
- take the average of the values
- use the origin
- choose the smallest value
- choose the largest value
-
When integer solutions are required, the vertex method may need
- ignoring the constraints
- using only the origin
- checking integer points near the optimal vertex
- rounding the objective function
-
The feasible region of a linear programme is always
- a non-convex star shape
- a convex region
- a single point
- a circle
-
If the objective line is parallel to an edge of the feasible region, then
- the problem is infeasible
- the optimum is at the origin
- there is no optimum
- every point on that edge gives the optimum, so there are many optima
-
Maximise P = 3x + 2y subject to x + y <= 4, x >= 0 and y >= 0. What is the maximum value of P?
- 4
- 8
- 12
- 16
-
With constraints 2x + y <= 10, x + 2y <= 8 and x, y >= 0, maximise P = x + y. What is the maximum and where is it?
- 4 at (0, 4)
- 5 at (5, 0)
- 6 at (4, 2)
- 7 at (3, 3)
-
Where do the lines 2x + y = 10 and x + 2y = 8 meet?
- (4, 2)
- (3, 4)
- (2, 4)
- (5, 0)
-
The linear programme optimum with an integer requirement lies at (2.5, 1.5). Which integer points should be checked first?
- (2.5, 1.5) only
- (0, 0) and (5, 3)
- (2, 3) and (3, 2)
- (2, 1), (2, 2), (3, 1) and (3, 2)
-
Objective P = 2x + 4y and constraint x + 2y <= 8 have parallel boundary slopes. What happens?
- the optimum is unique at (8, 0)
- there is no optimum
- every point on the edge x + 2y = 8 between its two vertices is optimal
- the optimum is at the origin
-
Minimise C = 2x + y subject to x + y >= 4 and x, y >= 0. What is the minimum?
- 8 at (4, 0)
- 4 at (0, 4)
- 0 at (0, 0)
- 6 at (2, 2)
-
Maximise P = 5x + 2y over a region with vertices (0, 0), (6, 0), (2, 5) and (0, 4). What is the maximum?
- 20
- 8
- 30
- 24
-
The feasible region is x >= 1, y >= 2 and x + y <= 6. What is the maximum value of x?
- 1
- 5
- 4
- 6
-
Maximise P = 3x + y with 2x + y <= 10, x + 2y <= 8 and x, y >= 0. What is the maximum?
- 15 at (5, 0)
- 16 at (4, 2)
- 4 at (0, 4)
- 14 at (4, 2)
-
Why can the vertex method fail when integer solutions are required?
- the integer optimum can lie strictly inside the region, away from every vertex
- objective lines have no slope
- vertices are never integers
- integer problems have no feasible region
-
Constraints x + y >= 6 and x + y <= 4 are imposed together. What does an empty feasible region mean?
- the problem has no feasible solution
- the optimum is at the origin
- the objective is zero
- there are infinitely many solutions
-
Maximise x + y subject to x - y <= 2 and x, y >= 0. What happens?
- the optimum is at (1, 1)
- the optimum is at (2, 0)
- the optimum is at the origin
- the objective is unbounded above
-
Maximise P = 4x + 3y subject to x + y <= 10, 2x + y <= 14 and x, y >= 0. What is the maximum?
- 30 at (0, 10)
- 34 at (4, 6)
- 28 at (7, 0)
- 36 at (6, 4)
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