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How to Fold a Square Sheet Into the Biggest Possible Open Box

Tell local maxima and minima from absolute extreme values and find critical points, classify them with the first and second derivative tests, and solve optimisation problems, including absolute extrema on a closed interval.

How do derivatives find the best possible value?

Engineers want the strongest beam from the least material; a shopkeeper wants the price that brings the most profit. These questions ask for a maximum or minimum.

This part covers local and absolute extrema with critical points, the first derivative test, the second derivative test, and optimisation problems.

How do local maxima and minima differ from absolute maximum and minimum values, and what are critical points?

**A local maximum or minimum is the highest or lowest value near a point, an absolute maximum or minimum is the greatest or least value over the whole domain or interval, and critical points — where or does not exist — are the only interior points where local extrema can occur.

Critical points.** If has a local extremum at an interior point and exists, then . So the candidates are points where or does not exist.

Worked example — not an extremum. has , but keeps increasing through , so is neither a maximum nor a minimum — it is a point of inflection.

An everyday example. A hilly trek passes many local peaks, but only one of them is the highest point of the whole route — the absolute maximum.

The substance. A local maximum can be lower than a local minimum elsewhere — local means best only nearby.

How does the first derivative test classify critical points?

**At a critical point , if changes from positive to negative as increases through , has a local maximum; if it changes from negative to positive, a local minimum; and if it does not change sign, neither.

Geometrically, the graph rises before a peak and falls after it.

Worked example.** has , with critical points and .

- Through , changes from to — a local maximum, with
- Through , changes from to — a local minimum, with

An everyday example. A cyclist riding over a flyover feels the road change from uphill to downhill exactly at the top — the sign change of the slope.

The substance. **The first derivative test also works where does not exist**, such as at , where the second derivative test cannot be used.

How does the second derivative test find local maxima and minima?

**If and , has a local maximum at ; if and , a local minimum; and if , the test fails and another method is needed.

Why it works.** means is decreasing near ; since , goes from positive to negative, giving a peak. gives a valley.

Worked example. For , .





An everyday example. A bowl sitting upright curves up and holds water at its lowest point, while an upturned bowl curves down with its highest point on top — like at a minimum and at a maximum.

The substance. ** does not mean there is no extremum** — it only means this test cannot decide.

How do you solve optimisation problems and find absolute extrema on a closed interval?

**Express the quantity to be optimised as a function of one variable, find its critical points and apply a derivative test; on a closed interval , compare the values at the critical points and at both endpoints to find the absolute maximum and minimum.

Worked example 1 — the open box.** Equal squares of side cm are cut from the corners of an cm square sheet, and the sides are folded up.



at , since leaves no box. With , , a maximum:



Worked example 2 — a closed interval. Find the absolute extrema of on .



The absolute maximum is at , and the absolute minimum is at .

An everyday example. A farmer fencing a rectangular plot beside a canal with a fixed length of wire uses exactly this method to enclose the largest area.

The substance. Absolute extrema on a closed interval often sit at the endpoints, which is why the endpoints must always be checked.
Exam tip

What earns full marks on maxima and minima?

State which test you are using, show the sign or value that decides it, and give word-problem answers with units.

- Critical points: or does not exist
- First derivative test: to maximum; to minimum; no change, neither
- Second derivative test: maximum; minimum; inconclusive
- Optimisation: one-variable function, derivative, test, answer in context

The trap. Ignoring the endpoints of a closed interval. **The absolute maximum or minimum may lie at an endpoint, where need not be zero.**
Did you know

Why are the cells of a honeycomb hexagonal?

Bees build their comb from wax, which takes a lot of energy to make. Dividing a flat surface into equal cells using the least total wall length is an optimisation problem.

Among the regular shapes that tile a flat surface with no gaps — triangles, squares and hexagons — hexagons enclose a given area with the shortest perimeter. So hexagonal cells hold the most honey for the least wax.

It is nature's own answer to exactly the kind of question solved in this lesson: getting the most from the least.
Exam relevance

How are maxima and minima tested in JEE Main?

Maxima and minima complete Application of Derivatives in JEE Main, and they bring together algebra, geometry and calculus.

What gets asked. Local and absolute extreme values of polynomial, trigonometric and exponential functions, optimising areas and volumes such as boxes, cones inscribed in spheres and nearest points on curves, and conditions on a parameter for a function to have extrema.

Question types. Numerical-value questions on maximum or minimum values, and multiple-choice questions on critical points.

The trap that costs marks. **Concluding there is no extremum when **, instead of switching to the first derivative test.
Key takeaways

What must you be able to do from this part?

- Extrema: local means best nearby, absolute means best overall; candidates are critical points where or does not exist
- First derivative test: to gives a maximum, to a minimum; has a maximum at and a minimum at
- Second derivative test: maximum, minimum, inconclusive
- Optimisation: an cm sheet makes a largest box of cm; on , compare critical values with endpoint values

Two positive numbers add up to . Find them if their product is to be as large as possible, and confirm your answer with the second derivative test.

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