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🎯⭐ INTERACTIVE LESSON

Optimization

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Optimization - Complete Interactive Lesson

Part 1: Setting Up Optimization Problems

Optimization

Part 1 of 7 — Setting Up Optimization Problems

Topic Overview

PartTopic
1Setting up optimization problems
2Geometric optimization
3Applied & business optimization
43D optimization (cylinders & cones)
5Distance & mixed optimization
6AP-style workshop
7Comprehensive assessment

The 5-Step Optimization Strategy

1. Variables→2. Objective→3. Constraint→4. Critical pts→5. Verify\boxed{\text{1. Variables} \to \text{2. Objective} \to \text{3. Constraint} \to \text{4. Critical pts} \to \text{5. Verify}}

StepActionExample
1. Define variablesLabel unknowns, draw a diagramx=x = width, y=y = length
2. Write objectiveFunction to max/minA=xyA = xy
3. Apply constraintEliminate one variable2x+y=200⇒y=200−2x2x + y = 200 \Rightarrow y = 200-2x
4. Find critical pointsSet f′(x)=0f'(x) = 0 and solveA′(x)=200−4x=0A'(x) = 200-4x = 0
5. Verify max/minSecond derivative or endpointsA′′(x)=−4<0⇒A''(x) = -4 < 0 \Rightarrow max

Worked Example: Rancher Fencing

A rancher has 200 m of fencing to enclose a rectangle along a river (no fence on the river side). Find the maximum area.

Let x=x = width, y=y = length along river.

Constraint: 2x+y=200⇒y=200−2x2x + y = 200 \Rightarrow y = 200 - 2x

Objective: A(x)=x(200−2x)=200x−2x2A(x) = x(200-2x) = 200x - 2x^2

A′(x)=200−4x=0⇒x=50A'(x) = 200 - 4x = 0 \quad \Rightarrow \quad x = 50

A′′(x)=−4<0A''(x) = -4 < 0 — concave down — maximum

y=200−100=100y = 200-100 = 100. Amax⁡=50×100=5000 m2\boxed{A_{\max} = 50 \times 100 = 5000 \text{ m}^2}

Key Fact: The optimal rectangle along a wall always has the side parallel to the wall equal to twice the perpendicular side.

Practice — Setting Up 🎯

Identify the setup. 🔍

Solve. ✍️

Key Takeaways — Part 1

  • Define variables clearly and draw a diagram
  • The objective is what you maximize/minimize
  • The constraint reduces to one variable
  • Use the Second Derivative Test or endpoint analysis to verify
  • AP Tip: Always state the domain of the objective function

Part 2: Geometric Optimization

Optimization

Part 2 of 7 — Geometric Optimization

Classic Geometry Problems

Problem TypeSetup
Box from sheetCut squares of side xx from corners, fold up
Rectangle in parabolaVertices at (±x,0)(\pm x, 0) and (±x,f(x))(\pm x, f(x))
Closest pointMinimize D2=(x−a)2+(f(x)−b)2D^2 = (x-a)^2 + (f(x)-b)^2
Inscribed shapesExpress dimensions using the curve equation

Worked Example: Open-Top Box

An open-top box is made by cutting squares of side xx from the corners of a 12×812 \times 8 sheet and folding up.

V(x)=x(12−2x)(8−2x)V(x) = x(12-2x)(8-2x)

Domain: 0<x<40 < x < 4

V=4x3−40x2+96xV = 4x^3 - 40x^2 + 96x V′(x)=12x2−80x+96=4(3x2−20x+24)V'(x) = 12x^2 - 80x + 96 = 4(3x^2 - 20x + 24)

x=20±400−2886=20±1126x = \frac{20 \pm \sqrt{400-288}}{6} = \frac{20 \pm \sqrt{112}}{6}

x≈1.57x \approx 1.57 (only solution in domain). Vmax⁡≈67.6 cubic units\boxed{V_{\max} \approx 67.6 \text{ cubic units}}

AP Tip: When asked to "set up but do not solve," write V(x)V(x), state the domain, and show V′(x)=0V'(x) = 0. You earn full credit without solving the quadratic.

Worked Example: Closest Point

Find the point on y=xy = \sqrt{x} closest to (3,0)(3, 0).

Minimize D2=(x−3)2+(x)2=(x−3)2+xD^2 = (x-3)^2 + (\sqrt{x})^2 = (x-3)^2 + x

ddxD2=2(x−3)+1=2x−5=0⇒x=52\frac{d}{dx}D^2 = 2(x-3) + 1 = 2x - 5 = 0 \quad \Rightarrow \quad x = \frac{5}{2}

Point: (52, 52)\left(\frac{5}{2},\, \sqrt{\frac{5}{2}}\right)

Key Fact: Always minimize D2D^2 instead of DD — it avoids square roots and gives the same critical points.

Practice — Geometric Optimization 🎯

Identify the correct approach. 🔍

Calculate. ✍️

Key Takeaways — Part 2

  • Box-cutting problems: V=x(L−2x)(W−2x)V = x(L-2x)(W-2x), domain 0<x<min⁡(L,W)/20 < x < \min(L,W)/2
  • Minimize D2D^2 for closest-point problems
  • Inscribed rectangle under a curve: A=2x⋅f(x)A = 2x \cdot f(x)
  • Always check domain endpoints for absolute max/min

Part 3: Cost & Revenue Optimization

Optimization

Part 3 of 7 — Applied & Business Optimization

Business Terminology

TermFormulaMeaning
RevenueR(x)=x⋅p(x)R(x) = x \cdot p(x)Income from selling xx units at price pp
CostC(x)C(x)Total cost to produce xx units
ProfitP(x)=R(x)−C(x)P(x) = R(x) - C(x)Revenue minus cost
Marginal costC′(x)C'(x)Cost of producing one more unit
Average costCˉ(x)=C(x)/x\bar{C}(x) = C(x)/xCost per unit

Max profit where R′(x)=C′(x)\boxed{\text{Max profit where } R'(x) = C'(x)}

Worked Example: Widget Company

A company sells widgets at price p=100−2xp = 100 - 2x per widget. Cost: C(x)=200+5xC(x) = 200 + 5x. Find maximum profit.

R(x)=x(100−2x)=100x−2x2R(x) = x(100-2x) = 100x - 2x^2 P(x)=R(x)−C(x)=100x−2x2−200−5x=−2x2+95x−200P(x) = R(x) - C(x) = 100x - 2x^2 - 200 - 5x = -2x^2 + 95x - 200 P′(x)=−4x+95=0⇒x=23.75P'(x) = -4x + 95 = 0 \quad \Rightarrow \quad x = 23.75

Since xx must be whole: P(24)=−2(576)+95(24)−200=−1152+2280−200=928P(24) = -2(576) + 95(24) - 200 = -1152 + 2280 - 200 = 928.

Pmax⁡=928 at x=24 widgets\boxed{P_{\max} = 928 \text{ at } x = 24 \text{ widgets}}, i.e. $928

AP Tip: On the AP exam, optimization word problems may use business language. Know the formulas for RR, CC, PP, and marginal quantities.

Practice — Applied Optimization 🎯

Classify the quantity. 🔍

Solve. ✍️

Key Takeaways — Part 3

  • Profit =R−C= R - C; max profit when R′(x)=C′(x)R'(x) = C'(x)
  • Average cost Cˉ=C(x)/x\bar{C} = C(x)/x; minimize by setting Cˉ′=0\bar{C}' = 0
  • Revenue R(x)=x⋅p(x)R(x) = x \cdot p(x) where p(x)p(x) is the demand function
  • When units must be integers, check both nearest whole numbers

Part 4: 3D Optimization (Cylinders & Cones)

Optimization

Part 4 of 7 — 3D Optimization (Cylinders & Cones)

3D Shape Formulas

ShapeVolumeSurface Area
Cylinder (closed)πr2h\pi r^2 h2πr2+2πrh2\pi r^2 + 2\pi rh
Cylinder (open top)πr2h\pi r^2 hπr2+2πrh\pi r^2 + 2\pi rh
Cone13πr2h\frac{1}{3}\pi r^2 hπr2+πrℓ\pi r^2 + \pi r\ell
Sphere43πr3\frac{4}{3}\pi r^34πr24\pi r^2

Worked Example: Minimize Surface Area

A closed cylinder has volume V=1000V = 1000 cm3^3. Find the radius that minimizes surface area.

Constraint: πr2h=1000⇒h=1000πr2\pi r^2 h = 1000 \Rightarrow h = \frac{1000}{\pi r^2}

Objective: S=2πr2+2πrh=2πr2+2000rS = 2\pi r^2 + 2\pi rh = 2\pi r^2 + \frac{2000}{r}

S′(r)=4πr−2000r2=0S'(r) = 4\pi r - \frac{2000}{r^2} = 0 4πr3=2000⇒r=(500π)1/3≈5.42 cm4\pi r^3 = 2000 \quad \Rightarrow \quad r = \left(\frac{500}{\pi}\right)^{1/3} \approx 5.42 \text{ cm}

Then h=1000π(5.42)2≈10.84≈2rh = \frac{1000}{\pi(5.42)^2} \approx 10.84 \approx 2r.

Optimal closed cylinder: h=2r\boxed{\text{Optimal closed cylinder: } h = 2r}

Key Fact: The optimal closed cylinder always has h=2rh = 2r (height equals diameter). For an open-top cylinder, the optimal ratio is h=rh = r.

Practice — 3D Optimization 🎯

Identify the setup. 🔍

Calculate. ✍️

Key Takeaways — Part 4

  • 3D optimization: same 5-step process with volume/surface area formulas
  • Closed cylinder: optimal when h=2rh = 2r
  • Open-top cylinder: optimal when h=rh = r
  • Always express SS or VV in one variable using the constraint

Part 5: Distance & Angle Optimization

Optimization

Part 5 of 7 — Distance & Mixed Problems

Distance Optimization

When minimizing the distance from a point (a,b)(a,b) to a curve y=f(x)y = f(x):

D2=(x−a)2+(f(x)−b)2\boxed{D^2 = (x-a)^2 + (f(x)-b)^2}

Key Fact: Always minimize D2D^2 — it shares the same critical points as DD and avoids square roots.

Worked Example: Wire-Cutting

A wire of length 20 is cut into two pieces. One is bent into a square, the other into a circle. What cut minimizes total area?

Let x=x = circumference of circle, 20−x=20-x = perimeter of square.

Circle: r=x2πr = \frac{x}{2\pi}, area =x24π= \frac{x^2}{4\pi}

Square: side =20−x4= \frac{20-x}{4}, area =(20−x)216= \frac{(20-x)^2}{16}

A(x)=x24π+(20−x)216A(x) = \frac{x^2}{4\pi} + \frac{(20-x)^2}{16}

A′(x)=x2π−20−x8=0A'(x) = \frac{x}{2\pi} - \frac{20-x}{8} = 0

4x8π=π(20−x)8π⇒4x=20π−πx\frac{4x}{8\pi} = \frac{\pi(20-x)}{8\pi} \quad \Rightarrow \quad 4x = 20\pi - \pi x

x=20ππ+4≈8.80x = \frac{20\pi}{\pi + 4} \approx 8.80

Special Optimization Patterns

PatternKey Idea
Max/min with absolute valueSplit into cases
Optimization on closed intervalCheck critical points AND endpoints
Profit with discrete unitsCheck both integers near the critical point
Constrained by two inequalitiesDomain may be restricted

Practice — Mixed Problems 🎯

Choose correctly. 🔍

Solve. ✍️

Key Takeaways — Part 5

  • Minimize D2D^2 for closest-point problems (avoids square roots)
  • Wire-cutting/splitting problems: express total in one variable
  • Closed interval: always check endpoints AND critical points
  • Discrete constraints: check both nearby integers

Part 6: AP-Style Workshop

Optimization

Part 6 of 7 — AP-Style Workshop

AP FRQ Optimization Patterns

PatternWhat They AskKey Steps
Geometric"Find dimensions that maximize/minimize..."Draw diagram, label, constrain
Applied"At what rate/quantity is profit maximized?"P=R−CP = R - C, set P′=0P' = 0
Justification"Justify that your answer is a maximum"Second derivative test or endpoints
Setup only"Write but do not solve..."Show objective, constraint, domain

Full Worked AP Problem

A rectangle has one side on the xx-axis, the upper two vertices on y=4−x2y = 4 - x^2.

(a) Express the area AA in terms of xx.

(b) Find the value of xx that maximizes AA.

(c) Justify that your answer gives a maximum.

Solution (a): Vertices at (±x,0)(\pm x, 0) and (±x,4−x2)(\pm x, 4-x^2). Width =2x= 2x, height =4−x2= 4-x^2. A(x)=2x(4−x2)=8x−2x3,0<x<2A(x) = 2x(4-x^2) = 8x - 2x^3, \quad 0 < x < 2

Solution (b): A′(x)=8−6x2=0⇒x2=4/3⇒x=23=233A'(x) = 8 - 6x^2 = 0 \Rightarrow x^2 = 4/3 \Rightarrow x = \frac{2}{\sqrt{3}} = \frac{2\sqrt{3}}{3}

Solution (c): A′′(x)=−12xA''(x) = -12x. At x=23/3x = 2\sqrt{3}/3: A′′=−12⋅233<0A'' = -12 \cdot \frac{2\sqrt{3}}{3} < 0.

Since A′′<0A'' < 0 at the critical point, AA is concave down there, so this gives a maximum.

Amax⁡=2⋅233(4−43)=433⋅83=3239A_{\max} = 2 \cdot \frac{2\sqrt{3}}{3}\left(4 - \frac{4}{3}\right) = \frac{4\sqrt{3}}{3} \cdot \frac{8}{3} = \frac{32\sqrt{3}}{9}

AP Tip: On justification, you must state the Second Derivative Test result AND explicitly conclude "maximum" or "minimum." Just computing f′′f'' is not enough.

AP-Style Practice 🎯

AP steps. 🔍

AP Problem. ✍️

Key Takeaways — Part 6

  • AP FRQs require complete justification for max/min
  • "Write but do not solve" earns credit for setup
  • Second Derivative Test is the standard justification
  • On closed intervals, compare all candidates (critical points + endpoints)

Part 7: Comprehensive Assessment

Optimization

Part 7 of 7 — Comprehensive Assessment

Optimization Strategy Reference

StepActionCheck
1Draw and label diagramVariables defined?
2Write objective functionWhat are you optimizing?
3Apply constraintDown to one variable?
4Find critical pointsf′(x)=0f'(x) = 0 solved?
5Verify max/min2nd derivative or endpoints?
6Answer the questionUnits included?

Common AP Mistakes

MistakeFix
Not stating the domainWrite 0<x<bound0 < x < \text{bound}
Forgetting to verify max vs minAlways use 2nd derivative test
Wrong constraintRe-read what's "fixed" or "given"
Ignoring endpoints on [a,b][a,b]Compare ff at all candidates
Not labeling unitsInclude m, cm2^2, etc.

Quiz Set 1 — Core Skills 🎯

Quiz Set 2 — Advanced Problems 🎯

Final review. 🔍

Final Challenge. ✍️

🎉 Topic Complete!

You've mastered Optimization:

PartTopicStatus
1Setting up optimization problems✅
2Geometric optimization✅
3Applied & business optimization✅
43D optimization (cylinders & cones)✅
5Distance & mixed problems✅
6AP-style workshop✅
7Comprehensive assessment✅

Key Fact: The 5-step optimization strategy (variables → objective → constraint → critical points → verify) works for every optimization problem. On the AP exam, always justify your answer using the Second Derivative Test or endpoint comparison.