Applications of Derivatives - Examples and Constructions
Optimization problems seek to maximize or minimize a quantity subject to constraints. These problems appear throughout science, engineering, economics, and everyday life, making them among the most practical applications of calculus.
A typical optimization problem involves:
- Objective function: The quantity to be maximized or minimized,
- Constraint(s): Conditions that restrict the domain, often given as equations or inequalities
- Critical point analysis: Finding where or doesn't exist
- Verification: Confirming which critical point gives the desired extremum
A rectangular box with a square base and open top is to have a volume of 32 cubic meters. Find the dimensions that minimize the amount of material used.
Let = side length of the square base, = height.
Constraint: , so
Surface area (objective function):
Domain: (physical constraint)
Setting :
So gives a minimum. Then .
Answer: Base meters, height meters.
A company can sell items per week at a price of dollars each. The cost of producing items is dollars. How many items should be produced to maximize profit?
Revenue:
Profit:
Setting :
So gives a maximum. The company should produce 160 items per week.
Steps for solving optimization problems:
- Draw a diagram if applicable
- Identify the quantity to optimize and express it as a function of one variable
- Use constraints to eliminate extra variables
- Find the domain of the objective function
- Compute the derivative and find critical points
- Use the first or second derivative test to classify extrema
- Check endpoints if the domain is closed
- Answer the question in context
Find the point on the parabola closest to the point .
Distance from to :
To simplify, minimize instead:
Critical points:
At : (local maximum) At : (local minimum)
The closest points are , each at distance from .
Optimization leverages the power of calculus to solve practical problems that would be intractable through trial and error or geometric reasoning alone.