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Max & Min Problems Simplified Revision Notes

Revision notes with simplified explanations to understand Max & Min Problems quickly and effectively.

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Max & Min Problems

We've seen how to derive the local minima and local maxima for a function. This has interesting applications in optimisation problems.

For example, a company produces xx cakes. The profit P(x)P(x), in euros, is modelled by the quadratic equation

P(x)=x2+10xP(x)=-x^2+10x

Let's graph this out :


image

From observation you can see a trade-off.

  • There's a portion of the graph where the company makes some amount of cakes, but could make more to increase the profit.
  • There's a portion of the graph where the company makes too much cakes such there profit starts to decrease, maybe because they can't sell the cakes. There is however a single point - the local maximum where the amount of cakes produced yields the highest possible profit.

Simply, derive P(x)P(x) :

P(x)=2x+10P'(x)=-2x+10

Now solve for P(x)=0P'(x)=0 :

2x+10=0-2x+10=0 x=5x=5

Producing 5 cakes yields the optimal amount of profit.

P(5)=(5)2+10(5)=25P(5)=-(5)^2+10(5)=25

25 euro is the optimal profit this company can produce.

Example

infoNote

An rectangular enclosure has a perimeter of 100 metres of fencing. The width of the enclosure is ww metres and the length of the enclosure is ll metres.

  1. Express ww in terms of ll.
  2. Find an expression for the area of the enclosure, in terms of ll
  3. Find the values of ll and ww that maximise the area of the enclosure.

The perimeter of the enclosure has to equal to 100 metres, which is how much fencing is available.

Hence, the perimeter can be written as :

2l+2w=1002l+2w=100

To express ww in terms of ll, simply isolate ww.

2w=1002l2w=100-2lw=50lw=50-l

We know that the area of a rectangle is the length, multiplied by the width.

Area=LW=lwArea =L \cdot W=l \cdot w

But we need to write this in terms of ll (i.e. there shouldn't be a ww term in there). In the first portion of the question, we found an expression for ww (in terms of ll) which we can substitute in.

Area=l(50l)=50ll2\begin{align*} Area &=l \cdot (50-l) \\\\ &= 50l-l^2 \end{align*}

Finally, we need to find the values of ll and ww that maximise the area of the enclosure. Find the first derivative of the AreaArea function :

Area=502lArea'=50-2l

Now solve for Area=0Area'=0 :

502l=050-2l=0l=25l=25

We know how long ll has to be. To find the corresponding ww, substitute back into the original expression for ww we found.

w=50lw=50-lw=50(25)w=50-(25)w=25w=25

Example

infoNote

A company needs to manufacture a cylindrical can that holds 1 litre (1000 cm³) of liquid. The cost of the material for the top and bottom is higher than for the side. Find the dimensions that minimize the cost of the material.

Let the radius of the base be rr and the height of the cylinder be hh. The volume constraint is :

πr2h=1000\pi r^2 h =1000

The cost function C(r)C(r) involves the surface area: C=2πr2C = 2\pi r^2 (for the top and bottom) plus 2πrh2\pi r h (for the side).

Next, set up the function that needs to be optimised, express hh from the volume constraint:

h=1000πr2 h = \frac{1000}{\pi r^2}

Substitute into the cost function :

C(r)=2πr2+2πr1000πr2=2πr2+2000r.C(r) = 2\pi r^2 + 2\pi r \cdot \frac{1000}{\pi r^2} = 2\pi r^2 + \frac{2000}{r}.

Differentiate the function :

C(r)=4πr2000r2C'(r) = 4\pi r - \frac{2000}{r^2}

Find the critical points by setting the derivative be equal to zero :

4πr2000r2=0 4\pi r - \frac{2000}{r^2} = 0 4πr3=2000 4\pi r^3 = 2000 r3=20004π=500πr=(500π)13 r^3 = \frac{2000}{4\pi} = \frac{500}{\pi} \quad \Rightarrow \quad r = \left(\frac{500}{\pi}\right)^{\frac{1}{3}}

Classify the critical points, i.e. use the second derivative test.

C(r)=4π+4000r3.C''(r) = 4\pi + \frac{4000}{r^3}.

Since C(r)>0C''(r) > 0, the cost function C(r)C(r) has a local minimum at this critical point.

The optimal radius is :

r=(500π)13.r = \left(\frac{500}{\pi}\right)^{\frac{1}{3}}.

The optimal height is :

h=1000πr2.h = \frac{1000}{\pi r^2}.
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