Maximum and minimum distance (lagrange multipliers)

In summary: The minimum distance from the origin to the given point is sqrt(4/3).In summary, the conversation discusses finding the minimum and maximum distances from the origin of a point that lies on a given plane and ellipsoid. The attempt at a solution involves using two constraints and solving for x, y, and z values. The conversation also mentions the possibility of incorrect calculations and the need to consider different values of mu. The correct minimum distance from the origin to the given point is sqrt(4/3).
  • #1
Gregg
459
0

Homework Statement



A point lies on the plane

x-y+z=0

and on the ellipsoid

[tex] x^2 +\frac{y^2}{4} + \frac{z^2}{4} = 1 [/tex]

Find the minimum and maximum distances from the origin of this point.


The Attempt at a Solution



The two contraints

[tex] g = x-y+z =h= x^2 +\frac{y^2}{4} + \frac{z^2}{4}-1=0 [/tex]

[tex] f = x^2+y^2+z^2 [/tex]



[tex] 2x = \lambda + 2\mu x [/tex]
[tex] 2y = -\lambda + \frac{1}{2}\mu y [/tex]
[tex] 2z = \lambda + \frac{1}{2}\mu z [/tex]

So y=-z?


From g:

[tex]x-y+z=0 \therefore x=2y=-2z [/tex]

from h:

[tex] 4y^2+\frac{1}{2}y^2=1\Rightarrow y = \pm\frac{\sqrt{2}}{3}[/tex]

[tex] z=\mp\frac{\sqrt{2}}{3}[/tex]

[tex] x=\pm\frac{2\sqrt{2}}{3}[/tex]

I'm not sure if this is correct.

The question asks for minimum and maximum but the distance function will give identical answers regardless of whether they are positive or negative. So I think I have done it wrong!
 
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  • #2
You found the minimum. I take it you did something like

[tex]y = -\frac{\lambda}{2(1-\mu/4)}[/tex]

[tex]z = \frac{\lambda}{2(1-\mu/4)}[/tex]

and came to your conclusion that y=-z. This logic works as long as [itex]\mu \ne 4[/itex], so you still have to consider what happens when [itex]\mu=4[/itex]. If you do that, you'll find the other solutions you were looking for.
 
  • #3
That is what I did, yes. If mu is 4 then from the 3 equations

[tex]2x = \lambda + 8x [/tex]

[tex]2y=-\lambda + 2y [/tex]

[tex]2z=\lambda + 2z [/tex]


I think that this implies that lambda is 0, and that x = 0.

from g: z=y

from h: [tex] z=y=\sqrt{2}[/tex]

A distance of 2 as opposed to the other extreme which is 14/9
 
  • #4
You also have the negative solutions, which results in the same distance of 2.

You calculated the minimum distance incorrectly. It should be sqrt(4/3).
 
  • #5
are the x,y and z values wrong for the minimum distance or have I made an error in the distance from correct x,y,z?
 
  • #6
Just in calculating the distance.
 

1) What is the concept of maximum and minimum distance in Lagrange multipliers?

The concept of maximum and minimum distance in Lagrange multipliers is based on finding the maximum and minimum values of a function subject to constraints. It involves using the method of Lagrange multipliers to determine the optimal distance between a point and a given set of points.

2) How is the method of Lagrange multipliers used to find the maximum and minimum distance?

The method of Lagrange multipliers involves setting up a function called the Lagrangian, which combines the original function with the constraints. Then, the partial derivatives of the Lagrangian are set equal to zero to find the critical points. These critical points are then checked to determine if they correspond to a maximum or minimum distance.

3) What are the applications of maximum and minimum distance in real-world problems?

Maximum and minimum distance in Lagrange multipliers have various applications in different fields such as economics, physics, and engineering. It can be used to optimize production processes, determine the most efficient use of resources, and find the shortest distance between two points in a three-dimensional space.

4) What is the role of Lagrange multipliers in optimization problems?

Lagrange multipliers play a crucial role in optimization problems by allowing us to incorporate constraints into the optimization process. It helps us find the maximum and minimum values of a function while satisfying the given constraints, making it a powerful tool in solving real-world problems.

5) Are there any limitations to using Lagrange multipliers to find maximum and minimum distance?

While Lagrange multipliers are a useful method for finding maximum and minimum distance, it is not always the most efficient approach. In some cases, it may be computationally intensive, and there may be alternative methods that can provide quicker solutions. Additionally, it may not be applicable to all types of constraints, such as inequalities or non-differentiable functions.

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