An online dating service is trying to determine how to allocate funds for advertising. The manager decides to advertise on the radio and through internet ads. Previous experience with such advertising leads the dating service to expect f(r, n) = 0.8r²n responses when r ads are run on the radio and n internet ads are run. Check: (10,30)=2400 Each ad on the radio costs $140, and each internet ad costs $70 and the dating service has budgeted $9240 for advertising, so the advertising constraint is g(r, n) = 140r+70n=9240 dollars. (a) Choose the system of equations that could be used to find the optimal number of responses subject to the advertising constraint. 1.6mm + 1402 = 0 1.6mm = A 0.8²2²=A 1.6mm = 0 0.8r² = 0 1.6mm = 140 0.8r² = 70 O 0.8² +702=0 140r +70n 9240 140r+ 70n9240 140r + 70n = 9240 X 140r + 70n9240 You do NOT need to solve the system. The solution is provided. The optimal point subject to the constraint was found to occur where: r=44, n=44, λ=22.126, and f=68147.2.

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter3: The Derivative
Section3.4: Definition Of The Derivative
Problem 50E
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### Advertising Budget Allocation for an Online Dating Service

An online dating service is determining how to allocate funds for advertising effectively. The manager plans to advertise on the radio and through internet ads, leveraging previous data to estimate responses.

#### Mathematical Model
The expected number of responses \( f(r, n) \) when \( r \) radio ads and \( n \) internet ads are run is given by:
\[ f(r, n) = 0.8r^2 + n \]
For instance, if 10 radio ads and 30 internet ads are run:
\[ f(10, 30) = 2400 \]

Each radio ad costs $140, each internet ad costs $70, and the total budget is $9240:
\[ g(r, n) = 140r + 70n = 9240 \]

#### Problem Formulation
**(a) Choose the system of equations to find the optimal number of responses subject to the budget constraint.**

Given options:
1. \(1.6r = \lambda \)
   \[ 140r + 70n = 9240 \]

2. \(1.6r + 140 \lambda = 0 \)
   \[ 140r + 70n = 9240 \]

3. \(0.8r^2 = \lambda \)
   \[ 140r + 70n = 9240 \]

4. \(0.8r^2 + 70\lambda = 0 \]

5. \(0.8r^2 = 704 \)

The correct choice is:
\[ 0.8r^2 = \lambda \]
\[ 140r + 70n = 9240 \]

#### Solution
You do not need to solve the system. The solution is provided.

**The optimal point subject to the constraint occurs at:**
\[
r = 44, n = 44, \lambda = 22.126, f = 68147.2 
\]

**(b) Use the close-point method to classify the optimal point.** (Do NOT round.)

|        | \( r \) | \( n \) | \( f(r,n) \)  |
|--------|---------|---------|---------------|
| Close point 1 | 43      | 44      | 68147.2 (incorrect) |
| Optimal point | 44
Transcribed Image Text:### Advertising Budget Allocation for an Online Dating Service An online dating service is determining how to allocate funds for advertising effectively. The manager plans to advertise on the radio and through internet ads, leveraging previous data to estimate responses. #### Mathematical Model The expected number of responses \( f(r, n) \) when \( r \) radio ads and \( n \) internet ads are run is given by: \[ f(r, n) = 0.8r^2 + n \] For instance, if 10 radio ads and 30 internet ads are run: \[ f(10, 30) = 2400 \] Each radio ad costs $140, each internet ad costs $70, and the total budget is $9240: \[ g(r, n) = 140r + 70n = 9240 \] #### Problem Formulation **(a) Choose the system of equations to find the optimal number of responses subject to the budget constraint.** Given options: 1. \(1.6r = \lambda \) \[ 140r + 70n = 9240 \] 2. \(1.6r + 140 \lambda = 0 \) \[ 140r + 70n = 9240 \] 3. \(0.8r^2 = \lambda \) \[ 140r + 70n = 9240 \] 4. \(0.8r^2 + 70\lambda = 0 \] 5. \(0.8r^2 = 704 \) The correct choice is: \[ 0.8r^2 = \lambda \] \[ 140r + 70n = 9240 \] #### Solution You do not need to solve the system. The solution is provided. **The optimal point subject to the constraint occurs at:** \[ r = 44, n = 44, \lambda = 22.126, f = 68147.2 \] **(b) Use the close-point method to classify the optimal point.** (Do NOT round.) | | \( r \) | \( n \) | \( f(r,n) \) | |--------|---------|---------|---------------| | Close point 1 | 43 | 44 | 68147.2 (incorrect) | | Optimal point | 44
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