Max/Min of x2−2xy+7y2 on Ellipse x2+4y2=1 w/ Lagrange Multiplier

Click For Summary

Homework Help Overview

The problem involves finding the maximum and minimum values of the function x² − 2xy + 7y² constrained by the ellipse x² + 4y² = 1, using the Lagrange Multiplier method.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the formulation of the Lagrange function and the necessity of certain variables. Questions arise regarding the inclusion of the variable z and the treatment of λ as a constant. There is also a mention of the process of finding critical points and evaluating them in the original function.

Discussion Status

The discussion is ongoing, with participants clarifying the setup of the Lagrange Multiplier method and addressing potential misconceptions. Some guidance has been provided regarding the formulation of the Lagrange function and the constraints involved.

Contextual Notes

Participants are navigating the specifics of the Lagrange Multiplier method, including the roles of variables and constraints, while adhering to the homework guidelines that may limit the depth of solutions discussed.

plexus0208
Messages
49
Reaction score
0

Homework Statement


Use the Lagrange Multiplier method to find the maximum and minimum values of x2 − 2xy + 7y2 on the ellipse x2 + 4y2 = 1.

Homework Equations


Lagrange multiplier method

The Attempt at a Solution


L(x,y,z,λ) = x2 − 2xy + 7y2 - λ(x2 + 4y2 - 1)
Find Lx, Ly, Lλ
Then, solve for x and y?
 
Last edited:
Physics news on Phys.org
Where did you get the L(x,y,z,λ)? You don't need the z in there because we're dealing with functions of x and y, not functions of x, y, and z.

Also, λ is a constant: you don't need to solve for Lλ. You don't need to solve for Lz either because there's no such variable as z. Just set Lx=0 and Ly=0 and solve. Don't forget to satisfy the initial constraint of x^2+4y^2=1!
 
Just an added note: some people are taught to find [itex]L_\lambda[/itex]. Because if we are trying to extremize F(x) subject to the constraint G(x)= 0, we look at [itex]L= F(x)+ \lambda G(x)[/itex], [itex]L_{\lamba}= G(x)= 0[/itex] is just the constraint again.
 
@ideasrule: Sorry, ignore the "z."
@HallsofIvy: Thanks. And yes, that's how I learned it.

Also, once I find the critical points, do I just plug them back into the original function I want to extremize to see if it's a max or min?
 

Similar threads

  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 13 ·
Replies
13
Views
2K
Replies
10
Views
1K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 1 ·
Replies
1
Views
5K
  • · Replies 13 ·
Replies
13
Views
4K