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Calculus 2nd Edition Rogawski

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854 C H A P T E R 15 DIFFERENTIATION IN SEVERAL VARIABLES<br />

In Theorem 1, the assumption ∇g P ̸= 0<br />

guarantees (by the Implicit Function<br />

Theorem of advanced calculus) that we can<br />

parametrize the curve g(x, y) = 0 near P<br />

by a path c such that c(0) = P and<br />

c ′ (0) ̸= 0.<br />

REMINDER Eq. (1) states that if a local<br />

min or max of f (x, y) subject to a<br />

constraint g(x, y) = 0 occurs at<br />

P = (a, b), then<br />

∇f P = λ∇g P<br />

provided that ∇g P ̸= 0.<br />

Proof Let c(t) be a parametrization of the constraint curve g(x, y) = 0 near P , chosen<br />

so that c(0) = P and c ′ (0) ̸= 0. Then f(c(0)) = f (P ), and by assumption, f(c(t)) has<br />

a local min or max at t = 0. Thus, t = 0 is a critical point of f(c(t)) and<br />

∣<br />

d ∣∣∣t=0<br />

dt f(c(t)) = ∇f P · c ′ (0) = 0<br />

} {{ }<br />

Chain Rule<br />

This shows that ∇f P is orthogonal to the tangent vector c ′ (0) to the curve g(x, y) = 0.<br />

The gradient ∇g P is also orthogonal to c ′ (0) (because ∇g P is orthogonal to the level<br />

curve g(x, y) = 0atP ). We conclude that ∇f P and ∇g P are parallel, and hence ∇f P is<br />

a multiple of ∇g P as claimed.<br />

We refer to Eq. (1) as the Lagrange condition. When we write this condition in terms<br />

of components, we obtain the Lagrange equations:<br />

f x (a, b) = λg x (a, b)<br />

f y (a, b) = λg y (a, b)<br />

Apoint P = (a, b) satisfying these equations is called a critical point for the optimization<br />

problem with constraint and f (a, b) is called a critical value.<br />

EXAMPLE 1 Find the extreme values of f (x, y) = 2x + 5y on the ellipse<br />

( x<br />

4<br />

) 2<br />

+<br />

( y<br />

3<br />

) 2<br />

= 1<br />

Solution<br />

Step 1. Write out the Lagrange equations.<br />

The constraint curve is g(x, y) = 0, where g(x, y) = (x/4) 2 + (y/3) 2 − 1. We have<br />

〈 x<br />

∇f = ⟨2, 5⟩ , ∇g =<br />

8 , 2y 〉<br />

9<br />

The Lagrange equations ∇f P = λ∇g P are:<br />

〈 x<br />

⟨2, 5⟩ = λ<br />

8 , 2y 〉<br />

⇒ 2 = λx 9<br />

8 , 5 = λ(2y)<br />

9<br />

Step 2. Solve for λ in terms of x and y.<br />

Eq. (2) gives us two equations for λ:<br />

λ = 16<br />

x , λ = 45<br />

2y<br />

To justify dividing by x and y, note that x and y must be nonzero, because x = 0or<br />

y = 0 would violate Eq. (2).<br />

Step 3. Solve for x and y using the constraint.<br />

The two expressions for λ must be equal, so we obtain 16<br />

x = 45 45<br />

or y = x. Now<br />

2y 32<br />

substitute this in the constraint equation and solve for x:<br />

(<br />

( x<br />

) 2 45<br />

+<br />

32 x<br />

) 2<br />

= 1<br />

4 3<br />

( 1<br />

x 2 16 + 225 ) ( ) 289<br />

= x 2 = 1<br />

1024 1024<br />

2<br />

3

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