Solving Maxima, Minima & Critical Points with Lagrange Multipliers & 2nd Derivative Test, Quizzes of Advanced Calculus

The solution to self-quiz 49 of math 210, which involves finding the maximum and minimum values of a function and identifying critical points using lagrange multipliers and the second derivative test. The problem includes finding the maximum and minimum values of x + 3y for points on an ellipse and analyzing the behavior of the function x² + y³ − 2y².

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2011/2012

Uploaded on 05/18/2012

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MATH 210
Self-quiz 49
1. Find the maximum and and minimum values of x+ 3y, for points on the
ellipse x2+ 4y2= 13. Use Lagrange multipliers, and also give the point(s)
where the max and min are attained.
2. Consider the function f(x, y) = x2+y4
2y2.
(a) Compute fx,fy,fxx,fxy and fyy .
(b) Find all critical points.
(c) Classify each critical point as a maximum, minimum or saddle.
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MATH 210

Self-quiz 49

  1. Find the maximum and and minimum values of x + 3y, for points on the ellipse x^2 + 4y^2 = 13. Use Lagrange multipliers, and also give the point(s) where the max and min are attained.
  2. Consider the function f (x, y) = x^2 + y^4 − 2 y^2.

(a) Compute fx, fy, fxx, fxy and fyy.

(b) Find all critical points.

(c) Classify each critical point as a maximum, minimum or saddle.

MATH 210

Self-quiz 49

  1. Find the maximum and and minimum values of x + 3y, for points on the ellipse x^2 + 4y^2 = 13. Use Lagrange multipliers, and also give the point(s) where the max and min are attained.

Solution: We will be using the method of Lagrange multipliers. To this end, we set:

f (x, y) = x + 3y g(x, y) = x^2 + 4y^2 − 13

and we consider the system:

{ ∇f = λ∇g g = 0

which can be rewritten as:

  

1 = 2λx 3 = 8λy x^2 + 4y^2 = 13

We solve for x and y to get:

x =

2 λ y =

8 λ

and then plug into the third equation to get:

4 λ^2

64 λ^2

that yields:

1 = 16λ^2 =⇒ λ = ±

To study the behaviour of the function at those points we will compute the determinant for the second derivative test. In general this determinant equals:

D =

∣∣ fxx^ fxy fxy fyy

0 12 y^2 − 4

∣∣ = 24y^2 − 8

So at (0, 0) we get D = − 8 < 0 which means that this is a saddle point. At (0, 1) we get D = 16 which means that we have a local extremum. In particular, since fxx(0, 1) = 2 > 0, this has to be a local minimum. Finally, at (0, −1) we get D = 16 and fxx(0, −1) which means that we have another local minimum.