Question

Difficulty: HardOptimization and Bounded Constraints

A research laboratory is formulating a daily dosage protocol for a clinical trial combining two therapeutics, Drug A (AA) and Drug B (BB), measured in integer milligrams (mg).

The trial protocol specifies the following operational constraints:
- The daily dosage of Drug A must be at least 10 mg10\text{ mg} and at most 40 mg40\text{ mg} (10A4010 \leq A \leq 40).
- The daily dosage of Drug B must be at least 15 mg15\text{ mg} and at most 50 mg50\text{ mg} (15B5015 \leq B \leq 50).
- To prevent hepatotoxicity, the combined daily dosage (A+B)(A + B) cannot exceed 65 mg65\text{ mg} (A+B65A + B \leq 65).
- To ensure therapeutic efficacy, the dosage of Drug B must be at least 10 mg10\text{ mg} less than twice the dosage of Drug A (B2A10B \geq 2A - 10).

The total treatment efficacy score EE is modeled by the linear function E=3A+4BE = 3A + 4B.

Based on the constraints above, select the daily dosage for Drug A and the daily dosage for Drug B that together maximize the total treatment efficacy score EE.

  • Daily Dosage of Drug A (mg)15
  • Daily Dosage of Drug B (mg)50

Answer

The optimal daily dosage is 15 mg for Drug A and 50 mg for Drug B, yielding a maximum total efficacy score of 245.
Because Drug B contributes +4+4 points per milligram to efficacy while Drug A contributes +3+3 points per milligram, maximizing Drug B to its upper limit of 50 mg provides the largest gain in total score. Given B=50 mgB = 50\text{ mg}, the combined toxicity limit A+B65 mgA + B \leq 65\text{ mg} restricts Drug A to at most 15 mg15\text{ mg}. Testing (A,B)=(15,50)(A, B) = (15, 50) satisfies all individual and joint constraints (151015 \geq 10, 502(15)10=2050 \geq 2(15) - 10 = 20), yielding the maximum overall score of 245245.

Step-by-Step Solution

1
Identify the objective function and system of linear inequalities.
Objective: Maximize E=3A+4BE = 3A + 4B subject to 10A4010 \leq A \leq 40, 15B5015 \leq B \leq 50, A+B65A + B \leq 65, and 2AB102A - B \leq 10.
Establishing the mathematical model allows systematically evaluating boundary vertices.
2
Analyze the objective function weights to determine optimization direction.
Drug B has a higher coefficient (+4+4) than Drug A (+3+3).
Increasing BB yields a greater increase in total efficacy EE per milligram than increasing AA, so BB should be made as large as allowed by constraints.
3
Test the maximum individual bound for Drug B.
Setting B=50B = 50 (its maximum bound), the toxicity constraint becomes A+5065    A15A + 50 \leq 65 \implies A \leq 15.
Determining the largest feasible AA given the maximal value of BB maximizes 3A+4(50)3A + 4(50).
4
Verify all secondary constraints at candidate point (A,B)=(15,50)(A, B) = (15, 50).
1) 10154010 \leq 15 \leq 40 (Satisfied)
2) 15505015 \leq 50 \leq 50 (Satisfied)
3) 15+50=656515 + 50 = 65 \leq 65 (Satisfied)
4) 502(15)10=2050 \geq 2(15) - 10 = 20 (Satisfied)
Total Efficacy: E=3(15)+4(50)=45+200=245E = 3(15) + 4(50) = 45 + 200 = 245.
Ensures the corner candidate point is fully compliant with every given restriction.
5
Compare against alternative valid vertex candidates.
Candidate (10,50)    E=30+200=230(10, 50) \implies E = 30 + 200 = 230.
Candidate (25,40)    E=75+160=235(25, 40) \implies E = 75 + 160 = 235.
Candidate (40,25)    E=120+100=220(40, 25) \implies E = 120 + 100 = 220.
Confirms that (15,50)(15, 50) yields the maximum value among all feasible integer combinations.

Key Concept

Optimization under Linear Inequality Bounded Constraints
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