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Sunday, September 13, 2026

📉 Maxima & Minima of Two-Variable Functions | f(x,y) = x² + y² + 6x + 12 | Stationary Points + Second Derivative Test 🧮 | Applied Calculus

Stationary Points of Two-Variable Functions — Worked Example

WORKED EXAMPLES2 · Engineering Mathematics 2 Solved Problems

Finding the Minimum of a Two‑Variable Function

Two full walkthroughs of stationary points and the second‑derivative test, applied to \(f(x,y) = x^2 + y^2 + 6x + 12\) and \(f(x,y) = x^2 - xy + y^2 - 2x + y\).

Topic · Maxima & Minima Level · Partial Differentiation Read time · 6 min
  • #PartialDerivatives
  • #StationaryPoints
  • #SecondDerivativeTest
  • #CalculusOfTwoVariables

Watch first — Example 2

Locating local maxima, minima, and saddle points for a function of two variables — a companion explainer on YouTube.

Before the algebra, the idea is simple: a smooth surface \(z = f(x,y)\) flattens out at its peaks, valleys, and saddles. Set both partial derivatives to zero to find those flat points, then use a second‑derivative test to tell which kind each one is.

📐 The worked examples

Two standard board questions, each solved step by step.

Example · stationary points and the AC − B² test

Find the minimum value of \(f(x,y) = x^2 + y^2 + 6x + 12\)JAN‑22‑R‑21

Step 1 — First partial derivatives

\[ f_x = \frac{\partial f}{\partial x} = 2x + 6 \qquad\qquad f_y = \frac{\partial f}{\partial y} = 2y \]

Step 2 — Locate the stationary point

\[ f_x = 0 \;\Rightarrow\; 2x + 6 = 0 \;\Rightarrow\; x = -3 \qquad\qquad f_y = 0 \;\Rightarrow\; 2y = 0 \;\Rightarrow\; y = 0 \]

The stationary point is \((-3,\,0)\).

Surface of \(f(x,y) = x^2+y^2+6x+12\) — the bowl bottoms out at the minimum, \((-3,\,0,\,3)\).

Step 3 — Second partial derivatives

\[ A = f_{xx} = \frac{\partial^2 f}{\partial x^2} = 2 \qquad B = f_{xy} = \frac{\partial^2 f}{\partial y\, \partial x} = 0 \qquad C = f_{yy} = \frac{\partial^2 f}{\partial y^2} = 2 \]

Step 4 — Classify the point

At \((-3,\,0)\)
A = 22 > 0
B = 00
C = 22
\(AC - B^2\)4 − 0 = 4 > 0
Minimum

Since \(AC - B^2 > 0\) and \(A > 0\), \((-3,\,0)\) is a minimum point.

Step 5 — Evaluate the minimum value

\[ f(-3,0) = (-3)^2 + 0^2 + 6(-3) + 12 = 9 - 18 + 12 = 3 \]
Minimum value of \(f(x,y)\), at \((-3,\,0)\) 3
Example 2 · stationary points and the \(rt - s^2\) test

Find the minimum value of \(f(x,y) = x^2 - xy + y^2 - 2x + y\)N/D‑22‑R‑21

Step 1 — First partial derivatives

\[ f_x = \frac{\partial f}{\partial x} = 2x - y - 2 \qquad\qquad f_y = \frac{\partial f}{\partial y} = -x + 2y + 1 \]

Step 2 — Locate the stationary point

\[ f_x = 0 \;\Rightarrow\; 2x - y = 2 \qquad\qquad f_y = 0 \;\Rightarrow\; x - 2y = -1 \]

Solving the two equations together gives \(x = 1\), \(y = 0\), so the stationary point is \((1,\,0)\).

Surface of \(f(x,y) = x^2-xy+y^2-2x+y\) — the tilted bowl bottoms out at the minimum, \((1,\,0,\,-1)\).

Step 3 — Second partial derivatives

\[ r = f_{xx} = \frac{\partial^2 f}{\partial x^2} = 2 \qquad s = f_{xy} = \frac{\partial^2 f}{\partial y\, \partial x} = -1 \qquad t = f_{yy} = \frac{\partial^2 f}{\partial y^2} = 2 \]

Step 4 — Classify the point

At \((1,\,0)\)
r = 22 > 0
s = −1−1
t = 22
\(rt - s^2\)4 − 1 = 3 > 0
Minimum

Since \(rt - s^2 > 0\) and \(r > 0\), \((1,\,0)\) is a minimum point.

Step 5 — Evaluate the minimum value

\[ f(1,0) = (1)^2 - (1)(0) + 0^2 - 2(1) + 0 = 1 - 2 = -1 \]
Minimum value of \(f(x,y)\), at \((1,\,0)\) −1

💡 Why this matters

Three things worth keeping from this example.

  • A stationary point only tells you where the surface is flat — the second‑derivative test tells you what kind of flat it is.
  • \(AC - B^2 > 0\) rules out a saddle; the sign of \(A\) (or \(C\)) then decides maximum versus minimum.
  • Completing the square confirms it instantly here: \(f(x,y) = (x+3)^2 + y^2 + 3\), which is never below 3.

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