12 multiple-choice questions, progressively harder.
In that bakery problem, the profit is 555 dollars per cake and 444 dollars per pie. What is the maximum profit?
Solution
Correct answer: B
The profit is P=5x+4yP = 5x + 4yP=5x+4y, largest at the corner (3,3)(3, 3)(3,3).
P(3,3)=5(3)+4(3)=15+12=27P(3, 3) = 5(3) + 4(3) = 15 + 12 = 27P(3,3)=5(3)+4(3)=15+12=27
So the maximum profit is 272727 dollars.
In that lamp and clock problem, the profit is 202020 dollars per lamp and 151515 dollars per clock. What is the maximum profit?
Correct answer: A
The profit P=20x+15yP = 20x + 15yP=20x+15y is largest at (3,2)(3, 2)(3,2).
P(3,2)=20(3)+15(2)=60+30=90P(3, 2) = 20(3) + 15(2) = 60 + 30 = 90P(3,2)=20(3)+15(2)=60+30=90
So the maximum profit is 909090 dollars.
For P=3x+2yP = 3x + 2yP=3x+2y with constraints x+y≤6x + y \le 6x+y≤6 and x≤4x \le 4x≤4 (and x,y≥0x, y \ge 0x,y≥0), is the plan (4,2)(4, 2)(4,2) feasible, and what is its objective value?
Correct answer: D
Check the constraints: x+y=6≤6x + y = 6 \le 6x+y=6≤6 and x=4≤4x = 4 \le 4x=4≤4, so (4,2)(4, 2)(4,2) is feasible. Now evaluate the objective.
P(4,2)=3(4)+2(2)=12+4=16P(4, 2) = 3(4) + 2(2) = 12 + 4 = 16P(4,2)=3(4)+2(2)=12+4=16
So the plan is feasible with value 161616.
Over x,y≥0x, y \ge 0x,y≥0 and x+y≥5x + y \ge 5x+y≥5, the objective P=2x+3yP = 2x + 3yP=2x+3y has:
The region runs up and to the right without bound, so P=2x+3yP = 2x + 3yP=2x+3y can be made as large as you like: no maximum. Its smallest value sits at the corner (5,0)(5, 0)(5,0), since (0,5)(0, 5)(0,5) gives 151515 but (5,0)(5, 0)(5,0) gives 101010.
minP=10 at (5,0),no maximum\min P = 10 \text{ at } (5, 0), \qquad \text{no maximum}minP=10 at (5,0),no maximum
So a minimum exists but no maximum.
Maximize P=x+3yP = x + 3yP=x+3y over x,y≥0x, y \ge 0x,y≥0, x+y≤6x + y \le 6x+y≤6, y≤4y \le 4y≤4. Which corner is optimal?
The corners are (0,0)(0, 0)(0,0), (6,0)(6, 0)(6,0), (0,4)(0, 4)(0,4), and the intersection of x+y=6x + y = 6x+y=6 with y=4y = 4y=4, which is (2,4)(2, 4)(2,4). Evaluate the objective.
P(6,0)=6,P(2,4)=14,P(0,4)=12P(6, 0) = 6, \qquad P(2, 4) = 14, \qquad P(0, 4) = 12P(6,0)=6,P(2,4)=14,P(0,4)=12
The maximum is at (2,4)(2, 4)(2,4).
Maximize P=3x+5yP = 3x + 5yP=3x+5y over x,y≥0x, y \ge 0x,y≥0, 2x+y≤102x + y \le 102x+y≤10, x+y≤7x + y \le 7x+y≤7. What is the maximum value?
Correct answer: C
The corners are (0,0)(0, 0)(0,0), (5,0)(5, 0)(5,0), (3,4)(3, 4)(3,4) (where 2x+y=102x + y = 102x+y=10 meets x+y=7x + y = 7x+y=7), and (0,7)(0, 7)(0,7). Evaluate the objective.
P(5,0)=15,P(3,4)=29,P(0,7)=35P(5, 0) = 15, \qquad P(3, 4) = 29, \qquad P(0, 7) = 35P(5,0)=15,P(3,4)=29,P(0,7)=35
The maximum value is 353535, at (0,7)(0, 7)(0,7).
The boundaries x+y=4x + y = 4x+y=4 and x+y=7x + y = 7x+y=7 come from two different constraints. Where do they meet?
Both lines have the same slope (rewrite as y=−x+4y = -x + 4y=−x+4 and y=−x+7y = -x + 7y=−x+7) but different intercepts.
x+y=4 ∥ x+y=7x + y = 4 \; \parallel \; x + y = 7x+y=4∥x+y=7
Parallel lines never cross, so there is no intersection point.
When can a linear objective have more than one optimal point on a bounded feasible region?
If the level lines match the slope of an edge, the last one to touch the region lies flat along that whole edge.
objective parallel to an edge ⇒ every point of that edge is optimal\text{objective parallel to an edge} \;\Rightarrow\; \text{every point of that edge is optimal}objective parallel to an edge⇒every point of that edge is optimal
Then both corners at the ends of the edge, and every point between them, tie for the best value.
Which point does NOT satisfy all of x≥0x \ge 0x≥0, y≥0y \ge 0y≥0, and 2x+3y≤122x + 3y \le 122x+3y≤12?
Test each point in 2x+3y≤122x + 3y \le 122x+3y≤12.
2(2)+3(3)=4+9=13>122(2) + 3(3) = 4 + 9 = 13 > 122(2)+3(3)=4+9=13>12
The point (2,3)(2, 3)(2,3) breaks the constraint. The others give 121212, 121212, and 121212, so they are all feasible.
Over the same region (x≤5x \le 5x≤5, y≤3y \le 3y≤3, x+y≤6x + y \le 6x+y≤6, x,y≥0x, y \ge 0x,y≥0), what is the maximum of P=x+4yP = x + 4yP=x+4y?
Evaluate P=x+4yP = x + 4yP=x+4y at the corners (5,0)(5, 0)(5,0), (5,1)(5, 1)(5,1), (3,3)(3, 3)(3,3), and (0,3)(0, 3)(0,3).
P(5,1)=9,P(3,3)=15,P(0,3)=12P(5, 1) = 9, \qquad P(3, 3) = 15, \qquad P(0, 3) = 12P(5,1)=9,P(3,3)=15,P(0,3)=12
The maximum is 151515, at (3,3)(3, 3)(3,3). Changing the objective moved the best corner away from (5,1)(5, 1)(5,1).
You invest xxx thousand dollars in stocks and yyy thousand in bonds, at most 101010 thousand in all, with at least 222 thousand in bonds. Besides x≥0x \ge 0x≥0 and y≥0y \ge 0y≥0, which constraints are correct?
The total investment is at most 101010, so x+y≤10x + y \le 10x+y≤10, and "at least 222 in bonds" means y≥2y \ge 2y≥2.
x+y≤10,y≥2x + y \le 10, \qquad y \ge 2x+y≤10,y≥2
The total is a ≤\le≤ limit (not forced equal), and the bond minimum is a ≥\ge≥ limit.
You must maximize a linear objective over a bounded feasible region. Which procedure is guaranteed to find the answer?
The corner-point principle guarantees the maximum sits at a vertex, so checking every vertex cannot miss it.
evaluate P at every vertex, then take the largest\text{evaluate } P \text{ at every vertex, then take the largest}evaluate P at every vertex, then take the largest
Testing the center, random interior points, or the corner nearest the origin can all miss the true best corner.
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