Table of contents
- 0. Functions7h 52m
- Introduction to Functions16m
- Piecewise Functions10m
- Properties of Functions9m
- Common Functions1h 8m
- Transformations5m
- Combining Functions27m
- Exponent rules32m
- Exponential Functions28m
- Logarithmic Functions24m
- Properties of Logarithms34m
- Exponential & Logarithmic Equations35m
- Introduction to Trigonometric Functions38m
- Graphs of Trigonometric Functions44m
- Trigonometric Identities47m
- Inverse Trigonometric Functions48m
- 1. Limits and Continuity2h 2m
- 2. Intro to Derivatives1h 33m
- 3. Techniques of Differentiation3h 18m
- 4. Applications of Derivatives2h 38m
- 5. Graphical Applications of Derivatives6h 2m
- 6. Derivatives of Inverse, Exponential, & Logarithmic Functions2h 37m
- 7. Antiderivatives & Indefinite Integrals1h 26m
- 8. Definite Integrals3h 25m
5. Graphical Applications of Derivatives
Applied Optimization
Problem 67
Textbook Question
Your company can manufacture x hundred grade A tires and y hundred grade B tires a day, where 0 ≤ x ≤ 4 and y = (40 - 10x)/(5-x). Your profit on a grade A tire is twice your profit on a grade B tire. What is the most profitable number of each kind to make?

1
First, understand the constraints: you can manufacture between 0 and 400 grade A tires (x hundred) and the number of grade B tires (y hundred) is given by the equation y = (40 - 10x)/(5-x).
Next, express the profit function. Let the profit on a grade B tire be P. Then, the profit on a grade A tire is 2P. The total profit function, in terms of x and y, is: Profit = 2Px + Py.
Substitute the expression for y from the constraint into the profit function: Profit = 2Px + P((40 - 10x)/(5-x)).
Simplify the profit function to express it solely in terms of x. This involves distributing and combining like terms.
Finally, determine the value of x that maximizes the profit function. This can be done by taking the derivative of the profit function with respect to x, setting it to zero, and solving for x. Check the endpoints x = 0 and x = 4 to ensure you have found the maximum profit within the given constraints.
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