Lagrange Multipler and Max/Min point of intersection

In summary: In order to do that here, they suggest taking f(x,y,z)= z so that \nabla f= <0,0,1>. Now we have to have <0,0,1>= \lambda <4,-3,8>+ \gamma <2x,2y,-2z> because of the constraint g(x,y,z)= 4x- 3y+ 8z- 5= 0. That gives us two equations, 0= 4\lambda+ 2\gamma x, 0= -3\lambda+ 2\gamma y, 1= 8\lambda- 2\gamma z. Since we have three equations in two
  • #1
calorimetry
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Homework Statement


The plane 4x − 3y + 8z = 5 intersects the cone z^2 = x^2 + y^2 in an ellipse.
Use LaGrange Multipliers to find the highest and lowest points on the ellipse.


Homework Equations


Lagrange Multiplier


The Attempt at a Solution


I guess I lack an understanding of Lagrange multiplier to begin solving this problem. Normally, I would be given some kinda of function express in term of x, y, and z and the plane would be the constraint for the function. Then I would just solve using Lagrange multiplier.

Here what is my function and what is my constrain?

I was thinking of using the cone as my function, but then I would have 0 = x^2 + y^2 - z^2
which is a surface and not a function of x, y, and z or is it?
And the plane is the constrain, but then I wouldn't be just looking for the max and min of the ellipse intersection anymore, it would be the max and min of the cone with the plane as the constrain.

I'm guessing both the plane and the cone are constrains in this problem because their intersection is the actual constrain, then what is my function to maximize/minimize?

Thanks in advance for any help/explanation.
 
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  • #2
how about trying the following (pretty much taken from what you described)

maximise
f(x,y,z) = z
subject to the constraints
g(x,y,z) = 4x − 3y + 8z - 5 = 0
h(x,y,z) = x^2 + y^2 - z^2 = 0

then use two lagrange multipliers...

[tex] F(x,y,z) = f + \lambda.g + \gamma.h [/tex]
then
[tex] \nablaF(x,y,z) = \nabla f + \lambda.\nabla g + \gamma.\nabla h [/tex]

gives 5 unknowns & 5 equations, though little messy not sure if there's an easier way, maybe using the z in the plane equation...
 
Last edited:
  • #3
Thanks lanedance, this is what I was thinking, but I don't know why I didn't realize that the function I am trying to maximize is f(x, y, z)=z. It should work.
 
  • #4
I don't get it... if you use f(x,y,z)=z to maximize, wouldn't you get fx(x,y,z)=0 and fy(x,y,z)=0... Then would you set fx(x,y,z) = fy(x,y,z)?
 
  • #5
xiseeux said:
I don't get it... if you use f(x,y,z)=z to maximize, wouldn't you get fx(x,y,z)=0 and fy(x,y,z)=0... Then would you set fx(x,y,z) = fy(x,y,z)?

true that fx(x,y,z)=0 and fy(x,y,z)=0, but then you use the lagrange multiplier method to get a set of equations to solve from
[tex] \nablaF(x,y,z) = \nabla f + \lambda.\nabla g + \gamma.\nabla h = 0 [/tex]
and the constraints
 
  • #6
xiseeux said:
I don't get it... if you use f(x,y,z)=z to maximize, wouldn't you get fx(x,y,z)=0 and fy(x,y,z)=0... Then would you set fx(x,y,z) = fy(x,y,z)?
You would if there were no constraints. And then, because the derivatives are always 0, you would get no "max" or "min"- f(z)= z has no maximum or minimum values.

But here the point is constrained to lie on two given figures. And you use "Lagrange multipliers" for problems like that.

If you want to maximize/minimize a function f(x,y,z) subject to the constraint g(x,y,z)= 0 then you must have [itex]\nabla f= \lambda \nabla g[/itex] for some "multiplier" [itex]\lambda[/itex].
 

1. What is a Lagrange Multiplier?

A Lagrange multiplier is a mathematical tool used in calculus to optimize a function subject to a set of constraints. It helps find the maximum or minimum value of a function while satisfying a given set of constraints.

2. How is a Lagrange Multiplier calculated?

To calculate a Lagrange multiplier, you must first set up a system of equations using the original function and the constraints. Then, use the method of partial derivatives to solve for the Lagrange multiplier. Once the value of the multiplier is found, it can be used to find the max/min point of intersection.

3. What is the significance of the max/min point of intersection obtained using a Lagrange Multiplier?

The max/min point of intersection obtained using a Lagrange Multiplier is significant because it represents the optimal solution to a problem, given the specified constraints. This point represents the maximum or minimum value of the function, depending on the problem at hand.

4. Can a Lagrange Multiplier be used for multivariable functions?

Yes, a Lagrange multiplier can be used for multivariable functions. In this case, the method of partial derivatives is used to find the max/min point of intersection in multiple dimensions.

5. Are there any real-world applications of Lagrange Multipliers?

Lagrange Multipliers have many real-world applications, including in economics, engineering, and physics. For example, they can be used to optimize production processes, design efficient structures, and determine the path of a particle under certain constraints.

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