Imagine, if you will, sitting in a classroom working out calculus problems on your test. And then, you come to it, the bane of many a calculus student: the dreaded maxima and minima word problem.
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Jetzt kostenlos anmeldenImagine, if you will, sitting in a classroom working out calculus problems on your test. And then, you come to it, the bane of many a calculus student: the dreaded maxima and minima word problem.
There is usually only one of these problems on your test – so you have only one shot to prove your skills – because they are so lengthy. Why are they like this? Of what use are they, really?
Well, just a few common applications of maxima and minima problems are:
to minimize cost and maximize profit,
to minimize or maximize areas,
to determine maximum or minimum values of an object in motion,
to help determine the dosage of a medicine, and
to help determine which materials to use when engineering something.
Now, if you found your way here from the maxima and minima article, great! If not, please refer to the maxima and minima article for a more in-depth introduction to the topic.
That being said, in this article, you will work through many examples of the application of derivatives known as maxima and minima problems.
First and foremost, what do maxima and minima look like?
Maxima are where a function has a high point, sometimes called a peak.
In turn,
Minima are where a function has a low point, sometimes called a valley.
Both maxima and minima can be included in a single term that is extrema.
Look at figure 1 to better clarify these terms.
Fig. 1 - The graph of the function \( f(x) = 2x^{3}-x^{5} \) has one local minimum, a saddle point, and one local maximum.
In a smooth function (i.e., one with no sharp points, breaks, or discontinuities) a maximum or minimum value is always where the function flattens out – except for a saddle point.
Before moving on, there are a couple of points of note regarding this graph.
First:
A saddle point is a critical point of a function that is neither a maximum nor a minimum.
In other words, a saddle point is a point on a function where the derivative is zero, but the point is not the highest or lowest in its area.
And, often, a saddle point looks much like the saddle on a horse. Hence, the name.
Second:
If you look carefully, you will see that the graph above does not have any absolute maxima or minima. This is because the function has a domain of \( (-\infty, \infty) \) and it extends towards infinity on both sides. To express this more formally,
a function that is defined on an open interval and whose left- and right-hand sides extend toward either positive or negative infinity has no absolute extrema.
For a more in-depth analysis and explanation of absolute extrema, please refer to the article on absolute maxima and minima.
Now that you know what maxima and minima look like, let's review the steps in solving maxima and minima problems. To do this, we will organize the steps into Strategy 1 and Strategy 2.
Let's start by looking at the first strategy.
Strategy 1 – Finding the Relative/Local Extrema of a Function
Now, let's move on to the second strategy.
Strategy 2 – Finding the Absolute/Global Extrema of a Function
To find the absolute extrema of a function, it must be continuous and defined over a closed interval \( [a, b] \).
In this section, you will work through examples where you identify the extrema of a given function graph.
Identify all the maxima and minima of the graph. You should assume that the graph represents the entire function, that is, it is on a closed interval.
Solution:
We can solve this example just by looking at the graph.
\( x \) | \( f(x) \) | Conclusion |
\( -3 \) | \( -1 \) | relative min |
\( -1.5 \) | \( 12 \) | absolute max |
\( 1.5 \) | \( -2 \) | absolute min |
\( 3 \) | \( 11 \) | relative max |
Let's look at another example.
Identify all the maxima and minima of the graph. You should assume that the graph represents the entire function, that is, it is on a closed interval.
Solution:
\( x \) | \( f(x) \) | Conclusion |
\( -3 \) | \( 66 \) | absolute max |
\( 0.25 \) | \( 3 \) | absolute min |
\( 1.4 \) | \( 8 \) | relative max |
\( 2.1 \) | \( 4 \) | relative min |
\( 2.75 \) | \( 13 \) | relative max |
\( 3 \) | \( 6 \) | relative min |
In this section, you will work through examples where you find the extrema of a given function.
Find the local extrema (maxima and minima) for the function,
\[ f(x) = x^{3} - 3x + 5. \]
Solution:
Here, you must apply Strategy 1.
Take the first derivative of the given function.\[ \begin{align}f'(x) &= \frac{\mathrm{d}}{\mathrm{d}x}(x^{3} - 3x + 5) \\ \\f'(x) &= 3x^{2} - 3\end{align} \]
Set \( f'(x) = 0 \) and solve for \( x \) to find all critical points.\[ \begin{align}f'(x) = 3x^{2} - 3 &= 0 \\ \\3(x^{2} - 1) &= 0 \\ \\(x - 1)(x + 1) &= 0 \\ \\x &= \pm 1\end{align} \]
Take the second derivative of the given function.\[ \begin{align}f''(x) = \frac{\mathrm{d}}{\mathrm{d}x}(f'(x)) &= \frac{\mathrm{d}}{\mathrm{d}x}(3x^{2} - 3) \\ \\f''(x) &= 6x\end{align} \]
Plug in the critical points from step 2 into the second derivative.
For \( x = -1 \),\[ f''(x) = 6(-1) = -6 \]Since \( -6 \) is negative, the critical point where \( x = -1 \) is a local maximum.
For \( x = 1 \),\[ f''(x) = 6(1) = 6 \]Since \( 6 \) is positive, the critical point where \( x = 1 \) is a local minimum.
To confirm your calculations, graph the function and plot the extreme values.
Therefore, the point \( (-1, 7) \) is a local maximum and the point \( (1, 3) \) is a local minimum.
Let's explore another example.
Find the absolute extrema (maximum and minimum) of the function,
\[ f(x) = x^{3} - 3x + 5 \]
over the closed interval \( [-3, 3] \).
Solution:
Here you must apply Strategy 2.
Since this is the same function that you used in the previous example, please refer to steps \( 1 \) through \( 4 \) of that example.
\( x \) | \( f(x) \) |
\( -3 \) | \( -13 \) |
\( -1 \) | \( 7 \) |
\( 1 \) | \( 3 \) |
\( 3 \) | \( 23 \) |
To confirm your calculations and comparisons, graph the function and plot the extrema.
Therefore, the point \( (-3, -13) \) is the absolute minimum and the point \( (3, 23) \) is the absolute maximum.
In this section – like the previous one – you will work through examples where you find the extrema of a function as a real-world application of taking derivatives. The difference here is how the information is presented to you. Following the format of a word problem, you will have to be able to determine what you need to do based on the context.
Say you launch a model rocket, and you know that the height of the rocket with respect to time is given by the formula
\[ H(t) = -6t^{2} + 120t \]
where,
Solutions:
Based on the given information, you know that:
Let's consider another example.
A manufacturing company finds that its profit from assembling a certain number of bicycles per day is given by the formula
\[ P(n) = -n^{2} + 50n - 100. \]
Solutions:
Based on the given information, you know that:
You solve maxima and minima problems by using the first and second derivatives of the original function. These are used in what are called the first derivative test and the second derivative test.
Maxima is the plural of maximum.
Minima is the plural of minimum.
You can find the relative minima or maxima of a function by using the first and second derivative tests.
Maxima and minima in calculus are the maximum and minimum values of a function. A function can have absolute or relative maxima or minima. Maxima and minima are known collectively as extrema.
A critical point in maxima and minima is a point that is either a maximum or minimum point of a function.
A function can have any number of absolute maxima and absolute minima on its domain.
False
A high point – also known as a peak – of a function is called a
Maximum (plural is maxima)
A low point – also known as a valley – of a function is called a
Minimum (plural is minima)
An extreme value of a function – also known as high or low point – is called a
Extremum (plural is extrema)
In a smooth function (i.e., one with no sharp points, breaks, or discontinuities) a maximum or minimum value is always where the function flattens out – except for
A saddle point
What are the steps for finding the relative (also called local) extrema (also known as maxima and minima) of a function?
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