Problem Overview
A civil engineering team designs an optimized perimeter and partition fencing layout for a 120 , 000 Β m 2 120,000\text{ m}^2 120 , 000 Β m 2 photovoltaic collection field. Outer security fencing costs $ 150 / m \$150/\text{m} $150/ m while two internal inverter dividing fences cost $ 50 / m \$50/\text{m} $50/ m . We minimize total construction cost using single-variable calculus and verify the global minimum using the Second Derivative Test.
Step-by-Step Mathematical Solution
Step 1: Formulate Governing Objective and Constraint Equations
The governing process follows the Applied Optimization Modeling Framework :
(Defined in Applied Optimization Modeling Framework .)
Geometry & Cost Allocation:
Outer boundary: 2 horizontal sides of length y y y and 2 vertical sides of length x x x . Unit cost = $ 150 / m = \$150/\text{m} = $150/ m .
Interior dividers: 2 vertical lines of length x x x . Unit cost = $ 50 / m = \$50/\text{m} = $50/ m .
Total cost of vertical segments (x x x ):
C x = ( 2 Γ 150 β
x ) + ( 2 Γ 50 β
x ) = 300 x + 100 x = 400 x C_x = (2 \times 150 \cdot x) + (2 \times 50 \cdot x) = 300x + 100x = 400x C x β = ( 2 Γ 150 β
x ) + ( 2 Γ 50 β
x ) = 300 x + 100 x = 400 x
Total cost of horizontal segments (y y y ):
C y = 2 Γ 150 β
y = 300 y C_y = 2 \times 150 \cdot y = 300y C y β = 2 Γ 150 β
y = 300 y
Total Cost Objective Function:
C ( x , y ) = 400 x + 300 y C(x, y) = 400x + 300y C ( x , y ) = 400 x + 300 y
Area Constraint Equation:
The total enclosed land footprint is fixed at 120 , 000 Β m 2 120,000\text{ m}^2 120 , 000 Β m 2 :
A = x β
y = 120 , 000 A = x \cdot y = 120,000 A = x β
y = 120 , 000
Step 2: Variable Reduction (Substitution)
Isolate y y y from the area constraint:
y = 120 , 000 x y = \frac{120,000}{x} y = x 120 , 000 β
Substitute into the cost objective function:
C ( x ) = 400 x + 300 ( 120 , 000 x ) = 400 x + 36 , 000 , 000 x = 400 x + 36 , 000 , 000 x β 1 C(x) = 400x + 300\left(\frac{120,000}{x}\right) = 400x + \frac{36,000,000}{x} = 400x + 36,000,000 x^{-1} C ( x ) = 400 x + 300 ( x 120 , 000 β ) = 400 x + x 36 , 000 , 000 β = 400 x + 36 , 000 , 000 x β 1
Step 3: Establish the Context-Driven Domain
(Governed by Context-Driven Domain in Geometric Optimization .)
Physical lengths must be positive: x > 0 x > 0 x > 0 .
As x β 0 x \to 0 x β 0 , y β β y \to \infty y β β and C ( x ) β β C(x) \to \infty C ( x ) β β .
As x β β x \to \infty x β β , y β 0 y \to 0 y β 0 and C ( x ) β β C(x) \to \infty C ( x ) β β .
Feasible domain is the open interval x β ( 0 , β ) x \in (0, \infty) x β ( 0 , β ) .
Step 4: Differentiate and Find Critical Numbers
Differentiate C ( x ) C(x) C ( x ) with respect to x x x using the Power Rule:
C β² ( x ) = d d x [ 400 x + 36 , 000 , 000 x β 1 ] = 400 β 36 , 000 , 000 x 2 C'(x) = \frac{d}{dx}\left[400x + 36,000,000 x^{-1}\right] = 400 - \frac{36,000,000}{x^2} C β² ( x ) = d x d β [ 400 x + 36 , 000 , 000 x β 1 ] = 400 β x 2 36 , 000 , 000 β
Set
C β² ( x ) = 0 C'(x) = 0 C β² ( x ) = 0 to identify stationary points:
400 β 36 , 000 , 000 x 2 = 0 400 - \frac{36,000,000}{x^2} = 0 400 β x 2 36 , 000 , 000 β = 0
400 = 36 , 000 , 000 x 2 400 = \frac{36,000,000}{x^2} 400 = x 2 36 , 000 , 000 β
400 x 2 = 36 , 000 , 000 400x^2 = 36,000,000 400 x 2 = 36 , 000 , 000
x 2 = 36 , 000 , 000 400 = 90 , 000 x^2 = \frac{36,000,000}{400} = 90,000 x 2 = 400 36 , 000 , 000 β = 90 , 000
x = 90 , 000 = 300 Β meters x = \sqrt{90,000} = 300\text{ meters} x = 90 , 000 β = 300 Β meters
(We reject the negative root x = β 300 Β m x = -300\text{ m} x = β 300 Β m because distance cannot be negative).
Step 5: Verify Absolute Global Minimum via Second Derivative Test
Compute the second derivative:
C β² β² ( x ) = d d x [ 400 β 36 , 000 , 000 x β 2 ] = 72 , 000 , 000 x 3 C''(x) = \frac{d}{dx}\left[400 - 36,000,000 x^{-2}\right] = \frac{72,000,000}{x^3} C β²β² ( x ) = d x d β [ 400 β 36 , 000 , 000 x β 2 ] = x 3 72 , 000 , 000 β
Evaluate at
x = 300 Β m x = 300\text{ m} x = 300 Β m :
C β² β² ( 300 ) = 72 , 000 , 000 ( 300 ) 3 = 72 , 000 , 000 27 , 000 , 000 = 8 3 > 0 C''(300) = \frac{72,000,000}{(300)^3} = \frac{72,000,000}{27,000,000} = \frac{8}{3} > 0 C β²β² ( 300 ) = ( 300 ) 3 72 , 000 , 000 β = 27 , 000 , 000 72 , 000 , 000 β = 3 8 β > 0
Since
C β² β² ( 300 ) > 0 C''(300) > 0 C β²β² ( 300 ) > 0 and
x = 300 Β m x = 300\text{ m} x = 300 Β m is the sole critical point in the domain
( 0 , β ) (0, \infty) ( 0 , β ) , the Second Derivative Test proves that
x = 300 Β m x = 300\text{ m} x = 300 Β m yields the unique
absolute minimum cost .
Step 6: Compute Optimal Dimensions and Total Construction Cost
Parallel Dimension (y y y ):
y = 120 , 000 300 = 400 Β meters y = \frac{120,000}{300} = 400\text{ meters} y = 300 120 , 000 β = 400 Β meters
Minimum Total Construction Expenditure:
C ( 300 ) = 400 ( 300 ) + 300 ( 400 ) = 120 , 000 + 120 , 000 = $ 240 , 000 C(300) = 400(300) + 300(400) = 120,000 + 120,000 = \$240,000 C ( 300 ) = 400 ( 300 ) + 300 ( 400 ) = 120 , 000 + 120 , 000 = $240 , 000
Notice the classic economic equipartition principle: at the cost-optimized optimum, total spending on vertical fencing (400 Γ 300 = $ 120 , 000 400 \times 300 = \$120,000 400 Γ 300 = $120 , 000 ) exactly balances total spending on horizontal fencing (300 Γ 400 = $ 120 , 000 300 \times 400 = \$120,000 300 Γ 400 = $120 , 000 ).