Question

Difficulty: MediumOptimization and Bounded Constraints

A boutique catering kitchen prepares custom corporate event packages containing two types of dessert selections: Specialty Layer Cakes (LL) and Miniature Cupcake Sets (MM). Each Specialty Layer Cake requires 33 hours of decorating labor and 44 kg of specialized flour. Each Miniature Cupcake Set requires 11 hour of decorating labor and 22 kg of specialized flour. For an upcoming event order, the kitchen has a maximum resource availability of 3030 total hours of decorating labor and 4444 kg of specialized flour. To meet client specifications, the kitchen must produce at least 44 Specialty Layer Cakes. If each Specialty Layer Cake yields a profit of $50\$50 and each Miniature Cupcake Set yields a profit of $20\$20, which of the following pairs of (L,M)(L, M) represents the combination of Specialty Layer Cakes and Miniature Cupcake Sets that maximizes total profit while satisfying all resource constraints?

  1. (8,6)(8, 6)Answer
  2. B
    (7,9)(7, 9)
  3. C
    (9,4)(9, 4)
  4. D
    (6,12)(6, 12)
  5. E
    (5,12)(5, 12)

Answer

The optimal production combination is 8 Specialty Layer Cakes and 6 Miniature Cupcake Sets, yielding a maximum profit of $520.
The pair (8,6)(8, 6) satisfies the minimum requirement of at least 4 Specialty Layer Cakes (848 \ge 4), requires 3(8)+1(6)=303(8) + 1(6) = 30 labor hours (within the 30-hour limit), and requires 4(8)+2(6)=444(8) + 2(6) = 44 kg of flour (within the 44-kg limit). It yields a total profit of 50(8)+20(6)=$52050(8) + 20(6) = \$520, which is the highest achievable profit among all feasible combinations.

Step-by-Step Solution

1
Formulate the mathematical model for constraints and objective function.
Decorating Labor: 3L+M303L + M \le 30; Specialized Flour: 4L+2M444L + 2M \le 44 (or 2L+M222L + M \le 22); Minimum Requirement: L4L \ge 4; Profit: P=50L+20MP = 50L + 20M.
Establishing explicit linear inequality bounds allows systematic evaluation of feasible integer pairs (L,M)(L, M).
2
Determine upper bound for MM as a function of integer values of L4L \ge 4.
For L=4L=4: Mmin(3012,228)=14    P=50(4)+20(14)=$480M \le \min(30-12, 22-8) = 14 \implies P = 50(4)+20(14) = \$480.
For L=5L=5: Mmin(3015,2210)=12    P=50(5)+20(12)=$490M \le \min(30-15, 22-10) = 12 \implies P = 50(5)+20(12) = \$490.
For L=6L=6: Mmin(3018,2212)=10    P=50(6)+20(10)=$500M \le \min(30-18, 22-12) = 10 \implies P = 50(6)+20(10) = \$500.
For L=7L=7: Mmin(3021,2214)=8    P=50(7)+20(8)=$510M \le \min(30-21, 22-14) = 8 \implies P = 50(7)+20(8) = \$510.
For L=8L=8: Mmin(3024,2216)=6    P=50(8)+20(6)=$520M \le \min(30-24, 22-16) = 6 \implies P = 50(8)+20(6) = \$520.
For L=9L=9: Mmin(3027,2218)=3    P=50(9)+20(3)=$510M \le \min(30-27, 22-18) = 3 \implies P = 50(9)+20(3) = \$510.
For L=10L=10: Mmin(3030,2220)=0    P=50(10)+20(0)=$500M \le \min(30-30, 22-20) = 0 \implies P = 50(10)+20(0) = \$500.
Evaluating potential corner points and boundary integer points identifies the maximum profit within the bounded region.
3
Compare maximum calculated profit across all valid integer pairs.
The highest profit occurs at L=8,M=6L = 8, M = 6 with P=$520P = \$520.
This point satisfies all constraints while maximizing the objective function.

Key Concept

Optimization under multiple joint inequality constraints
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