Recall that differentiation is about the rate of change of a function and provides a way of finding minimum and maximum values of a function
Anything that involves maximising or minimising a quantity can be modelled using differentiation; for example
minimising the cost of raw materials in manufacturing a product
the maximum height a football could reach when kicked
These are called optimisation problems
What modelling assumptions are used in optimisation problems?
The quantity being optimised needs to be dependent on a single variable
If other variables are initially involved, constraints or assumptions about them will need to be made; for example
minimising the cost of the main raw material – timber in manufacturing furniture say – the cost of screws, glue, varnish, etc can be fixed or considered negligible
Other modellingassumptions may have to be made too; for example
ignoring air resistance and wind when modelling the path of a kicked football
How do I solve optimisation problems?
Problems often start by linking two connected quantities together – for example volume and surface area
where more than one variable is involved, constraints will be given such that the quantity of interest can be rewritten in terms of a single variable
Once the quantity of interest is written as a function of a single variable, differentiation can be used to maximise or minimise the quantity as required
STEP 1
Rewrite the quantity to be optimised as a single variable, using any constraints given in the question
STEP 2
Use your GDC to find the (local) maximum or minimum points as required
Plot the graph of the function and use the graphing features of the GDC to “solve for minimum/maximum” as required
STEP 3
Note down the solution from your GDC and interpret the answer(s) in the context of the question
Exam Tip
The first part of rewriting a quantity as a single variable is often a “show that” question – this means you may still be able to access later parts of the question even if you can’t do this bit