Optimization: Maximum Volume Box with Fixed Material

Optimization & Calculus 11th-12th Grade
Problem
We have 45 m² of material to build a box with a square base and no top. Determine the dimensions of the box that will maximize the enclosed volume.

Visualizing the Problem

We have 45 m² of material to build a box with a square base and no top. Determine the dimensions of the box that will...

What This Problem Teaches

  • Constraint optimization using single-variable calculus — Converting a two-variable problem into an optimization on one variable
  • Physical interpretation of mathematical constraints — Understanding how material limitations translate into algebraic equations
  • Critical point analysis and the second derivative test — Confirming that a critical point represents a maximum rather than a minimum
  • Geometric optimization principles — Discovering the optimal proportions that emerge from mathematical optimization
  • Domain considerations in applied problems — Recognizing that physical constraints limit the valid range of solutions

Solution: Method 1 — Single-Variable Calculus

This is a classic constrained optimization problem. We need to find the dimensions that give maximum volume while respecting the constraint on available material.

Step 1 — Define Variables and Set Up the Constraint

Let x be the side length of the square base (in meters) and h be the height of the box (in meters). Since there's no top, the material is used for:

  • Base: square meters
  • Four sides: 4xh square meters

The constraint equation is:

x² + 4xh = 45

Step 2 — Express Volume as a Function of Both Variables

The volume of the box is:

V = x²h

Step 3 — Eliminate One Variable Using the Constraint

From the constraint equation, solve for h:

x² + 4xh = 45
4xh = 45 - x²
h = (45 - x²)/(4x)

Substitute this into the volume function:

V(x) = x² · (45 - x²)/(4x)
V(x) = x(45 - x²)/4
V(x) = (45x - x³)/4

Step 4 — Find Critical Points

Take the derivative and set it equal to zero:

V'(x) = (45 - 3x²)/4
Setting V'(x) = 0:
45 - 3x² = 0
3x² = 45
x² = 15
x = √15 ≈ 3.87 meters

Step 5 — Verify This Is a Maximum

Check the second derivative:

V''(x) = -6x/4 = -3x/2
V''(√15) = -3√15/2 ≈ -5.81 < 0

Since the second derivative is negative, this critical point represents a maximum.

Step 6 — Find the Corresponding Height

Using x = √15 in our constraint:

h = (45 - x²)/(4x)
h = (45 - 15)/(4√15)
h = 30/(4√15) = 30√15/60 = √15/2 ≈ 1.94 meters

Step 7 — Calculate Maximum Volume

V = x²h = 15 · (√15/2) = 15√15/2 ≈ 29.05 m³
Base side length: x = √15 ≈ 3.87 meters
Height: h = √15/2 ≈ 1.94 meters
Maximum volume: 15√15/2 ≈ 29.05 m³

Solution: Method 2 — Lagrange Multipliers

For students comfortable with multivariable calculus, we can solve this as a constrained optimization problem using Lagrange multipliers.

Step 1 — Set Up the Lagrangian

We want to maximize f(x,h) = x²h subject to g(x,h) = x² + 4xh - 45 = 0.

The Lagrangian is:

L(x, h, λ) = x²h - λ(x² + 4xh - 45)

Step 2 — Find the Gradient Conditions

Set all partial derivatives equal to zero:

∂L/∂x = 2xh - λ(2x + 4h) = 0
∂L/∂h = x² - λ(4x) = 0
∂L/∂λ = -(x² + 4xh - 45) = 0

Step 3 — Solve the System

From the second equation: λ = x²/(4x) = x/4

Substituting into the first equation:

2xh - (x/4)(2x + 4h) = 0
2xh - (x²/2 + xh) = 0
2xh - x²/2 - xh = 0
xh - x²/2 = 0
h = x/2

Step 4 — Apply the Constraint

Substitute h = x/2 into the constraint:

x² + 4x(x/2) = 45
x² + 2x² = 45
3x² = 45
x = √15

This gives us the same result: x = √15 and h = √15/2.

Verification

Let's verify our answer satisfies the constraint and gives the stated volume:

Material check: x² + 4xh = (√15)² + 4(√15)(√15/2)
= 15 + 4 · 15/2 = 15 + 30 = 45 ✓

Volume check: V = x²h = (√15)² · (√15/2)
= 15 · √15/2 = 15√15/2 ≈ 29.05 m³ ✓
Reality Check: These dimensions make intuitive sense. The optimal height (≈1.94 m) is exactly half the base side length (≈3.87 m). This 1:2 ratio isn't arbitrary—it's the precise balance between base area and side area that maximizes volume under our material constraint.

Where Students Go Wrong

✗ Forgetting the constraint completely
Some students try to maximize V = x²h by taking partial derivatives with respect to both variables, getting ∂V/∂x = 2xh = 0 and ∂V/∂h = x² = 0. This gives the nonsensical solution x = 0 or h = 0 because it ignores the material constraint entirely.
✗ Including the top in the surface area calculation
A common error is writing the constraint as x² + x² + 4xh = 45 (counting the top). The problem clearly states "no top," so only the base and four sides use material. This error leads to h = (45 - 2x²)/(4x) and incorrect final dimensions.
✗ Not checking the second derivative
Finding that V'(x) = 0 when x = √15 is necessary but not sufficient. Without verifying V''(√15) < 0, you haven't confirmed this is a maximum rather than a minimum. In optimization problems, this verification step is crucial.
✗ Ignoring domain restrictions
The constraint h = (45 - x²)/(4x) requires h ≥ 0, which means 45 - x² ≥ 0, so x ≤ 3√5 ≈ 6.71. Also, x > 0 for a physical box. Students sometimes don't verify their solution lies within this valid domain.

The Pattern Behind This

This problem illustrates the general approach to constrained optimization in single-variable calculus:

Given: Optimize f(x,y) subject to g(x,y) = c
1. Solve the constraint for one variable: y = h(x)
2. Substitute: F(x) = f(x, h(x))
3. Find critical points: F'(x) = 0
4. Verify maximum/minimum: F''(x) < 0 or > 0
5. Check endpoint behavior if domain is bounded

The beautiful result h = x/2 emerges from the specific constraint structure. When material is allocated optimally, the base area equals twice the total side area: x² = 2(4xh)/4 = 2xh, giving h = x/2.

Key Insight: In optimization problems involving surface area and volume, optimal solutions often exhibit elegant proportional relationships. The 1:2 ratio between height and base side isn't a design choice—it's mathematics telling us how nature minimizes waste.

Real Applications

  • Manufacturing and packaging: Companies use these calculations to minimize material costs while maximizing product capacity, from shipping containers to food packaging.
  • Architecture and construction: Designing storage tanks, silos, and buildings where material costs must be balanced against functional volume requirements.
  • 3D printing and rapid prototyping: Optimizing designs to minimize filament usage while maintaining structural integrity and maximum internal volume.

What If?

1Different Material Amount
You have 72 m² of material to build a box with a square base and no top. What dimensions maximize the volume?
Step 1 — Set up with new constraint

Constraint: x² + 4xh = 72, so h = (72 - x²)/(4x)

Step 2 — Volume function

V(x) = x² · (72 - x²)/(4x) = (72x - x³)/4

Step 3 — Find critical points

V'(x) = (72 - 3x²)/4 = 0, so x² = 24, giving x = 2√6 ≈ 4.90 m

Step 4 — Find height

h = (72 - 24)/(4 · 2√6) = 48/(8√6) = √6 ≈ 2.45 m

Step 5 — Calculate maximum volume

V = x²h = 24 · √6 = 24√6 ≈ 58.79 m³

Verification

Material: (2√6)² + 4(2√6)(√6) = 24 + 48 = 72 ✓

Answer: Base = 2√6 ≈ 4.90 m, Height = √6 ≈ 2.45 m, Volume = 24√6 ≈ 58.79 m³

2Fixed Volume, Minimize Material
You want a box with square base, no top, and volume exactly 32 m³. What dimensions minimize the material used?
Step 1 — Set up the volume constraint

Constraint: x²h = 32, so h = 32/x²

Step 2 — Material function

M(x) = x² + 4xh = x² + 4x(32/x²) = x² + 128/x

Step 3 — Minimize material

M'(x) = 2x - 128/x² = 0, so 2x³ = 128, giving x³ = 64, thus x = 4 m

Step 4 — Find height

h = 32/x² = 32/16 = 2 m

Step 5 — Calculate minimum material

M = x² + 4xh = 16 + 4(4)(2) = 16 + 32 = 48 m²

Verification

Volume: 4² × 2 = 32 m³ ✓
Second derivative: M''(4) = 2 + 256/64 = 6 > 0 (minimum) ✓

Answer: Base = 4 m, Height = 2 m, Material = 48 m²

3Double-Thick Base
The base must be double thickness (uses twice as much material per unit area), but you still have 45 m² total. Find the volume-maximizing dimensions.
Step 1 — New constraint equation

Base uses 2x² (double thickness), sides use 4xh
Constraint: 2x² + 4xh = 45

Step 2 — Solve for height

4xh = 45 - 2x², so h = (45 - 2x²)/(4x)

Step 3 — Volume function

V(x) = x² · (45 - 2x²)/(4x) = (45x - 2x³)/4

Step 4 — Find critical points

V'(x) = (45 - 6x²)/4 = 0, so x² = 7.5, giving x = √7.5 = √(30/4) = √30/2 ≈ 2.74 m

Step 5 — Calculate dimensions

h = (45 - 2(7.5))/(4√30/2) = 30/(2√30) = √30/2 ≈ 2.74 m
V = (7.5)(√30/2) = 7.5√30/2 ≈ 20.54 m³

Verification

Material: 2(7.5) + 4(√30/2)(√30/2) = 15 + 30 = 45 ✓

Answer: Base = √30/2 ≈ 2.74 m, Height = √30/2 ≈ 2.74 m, Volume ≈ 20.54 m³

4Given Dimensions, Find Material
Reverse engineering: If the optimal box from the original problem (base √15 m, height √15/2 m) were built with a top included, how much total material would be needed?
Step 1 — Identify the known dimensions

Base side length: x = √15 m
Height: h = √15/2 m

Step 2 — Calculate each surface

Base area: x² = (√15)² = 15 m²
Top area: x² = 15 m²
Four sides: 4xh = 4(√15)(√15/2) = 4 × 15/2 = 30 m²

Step 3 — Sum total material

Total material = Base + Top + Sides
= 15 + 15 + 30 = 60 m²

Step 4 — Compare to original problem

Original (no top): 45 m²
With top: 60 m²
Additional material needed: 60 - 45 = 15 m²

Step 5 — Verify the calculation

The top area should equal the base area: √15 × √15 = 15 m²
This makes sense because both are squares with side length √15.

Insight

Notice that the additional material (15 m²) equals exactly one-third of the original material (45 m²). This reflects the optimal 1:2 ratio between height and base—the top area is exactly 1/3 of the original surface area.

Answer: Total material with top = 60 m² (15 m² more than the no-top version)

Frequently Asked Questions

How do you set up a calculus optimization problem with material constraints?+

First, identify your objective function (what you want to maximize or minimize) and your constraint equation. Express both in terms of the same variables, then use the constraint to eliminate one variable from the objective function. In this problem, we maximize volume V = x²h subject to the material constraint x² + 4xh = 45, which lets us write h in terms of x and create a single-variable function to optimize.

When do you use the first derivative test versus the second derivative test?+

Use the first derivative test to find critical points by setting f'(x) = 0. Use the second derivative test to classify those critical points: if f''(x) > 0, it's a minimum; if f''(x) < 0, it's a maximum. In this box problem, we find f'(x) = 0 gives x = √15, then f''(√15) = -3√15/2 < 0 confirms this is indeed a maximum.

Why does the optimal box have height equal to half the base side length?+

This ratio emerges from the specific constraint structure. When material is fixed at x² + 4xh = 45 and we maximize x²h, calculus shows that optimal allocation occurs when the base area (x²) equals twice the total side area (4xh). This gives x² = 2(4xh)/4 = 2xh, so h = x/2. The 1:2 ratio is a beautiful consequence of the mathematical optimization, not an arbitrary design choice.

DN

Dr. Neven Jurkovic

Mathematics Professor specializing in calculus and optimization. Expert in making complex mathematical concepts accessible through real-world applications.

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Neven Jurkovic, PhD

Professor of Computer Science, Palo Alto College, Alamo Colleges District, San Antonio, TX

Developer of Algebrator

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This solution was prepared with AI assistance and reviewed by Dr. Jurkovic for mathematical accuracy and pedagogical clarity.

2026-08-12