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Last Updated Sep 27, 2025
Revision notes with simplified explanations to understand Max & Min Problems quickly and effectively.
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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 cakes. The profit , in euros, is modelled by the quadratic equation
Let's graph this out :
From observation you can see a trade-off.
Simply, derive :
Now solve for :
Producing 5 cakes yields the optimal amount of profit.
25 euro is the optimal profit this company can produce.
Example
An rectangular enclosure has a perimeter of 100 metres of fencing. The width of the enclosure is metres and the length of the enclosure is metres.
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 :
To express in terms of , simply isolate .
We know that the area of a rectangle is the length, multiplied by the width.
But we need to write this in terms of (i.e. there shouldn't be a term in there). In the first portion of the question, we found an expression for (in terms of ) which we can substitute in.
Finally, we need to find the values of and that maximise the area of the enclosure. Find the first derivative of the function :
Now solve for :
We know how long has to be. To find the corresponding , substitute back into the original expression for we found.
Example
Let the radius of the base be and the height of the cylinder be . The volume constraint is :
The cost function involves the surface area: (for the top and bottom) plus (for the side).
Next, set up the function that needs to be optimised, express from the volume constraint:
Substitute into the cost function :
Differentiate the function :
Find the critical points by setting the derivative be equal to zero :
Classify the critical points, i.e. use the second derivative test.
Since , the cost function has a local minimum at this critical point.
The optimal radius is :
The optimal height is :
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