Solve Crazy Lagrange Problem: Min Distance from Origin

  • Thread starter daBish
  • Start date
  • Tags
    Lagrange
In summary, on a test, the question was given to find the minimum distance from the origin using the Lagrange method with a constraint equation of z^2-xy+1=0. This is done by minimizing D^2=x^2+y^2+z^2 with the given constraint using partial derivatives. After solving for k and using the relationship between x and y, the solution can be found as x=+/-2, y=+/-2, z=0.
  • #1
daBish
2
0
--------------------------------------------------------------------------------

Ok this is the question I had on a test today:

given this constraint equation z^2-xy+1=0 find the min. distance from the origin using Lagrange method.

so basically you use D^2=x^2+y^2+z^2 as the other equation. however, it basically goes nuts from there. especially if you set it up like you are suppose to.
Fx=(lambda)Gx
Fy=(lambda)Gy
Fz=(lambda)Gz
g=0

(capitals are partial derivatives)

with f as the distance formual and g as the constraint

this one sucks but if someone could help it would be greatly appreciated
 
Physics news on Phys.org
  • #2
Minimizing D is the same as minimizing D^2, so we solve

2x = -ky
2y=-kx
2z=2kz

whence k=1, x=-y, which leads to nonsense, or z=0, and 2x=-ky=k^2x, so k=sqrt(2), also note that xy=1, and the solution follows.

edit, thanks to arildno, it should read:

2x=-ky=k^2x/2, ie

4x=xk^2, whence k=+/-2

from which you should be able to get the answer.
 
Last edited:
  • #3


The Lagrange method is a powerful tool for solving constrained optimization problems, but it can be quite challenging to apply, especially in more complex problems. In this case, we are trying to find the minimum distance from the origin, subject to the constraint z^2-xy+1=0. This means that we are trying to minimize the function f(x,y,z) = x^2 + y^2 + z^2, while satisfying the constraint g(x,y,z) = z^2-xy+1=0.

To solve this problem, we first set up the Lagrangian function L(x,y,z,λ) = f(x,y,z) - λg(x,y,z). This function represents the trade-off between the objective function (minimizing distance) and the constraint (satisfying the given equation). The parameter λ is known as the Lagrange multiplier, and it helps us incorporate the constraint into our optimization problem.

Next, we take the partial derivatives of L with respect to x, y, z, and λ, and set them equal to 0. This will give us a system of equations that we can solve to find the optimal values for x, y, z, and λ. Once we have these values, we can plug them back into the original objective function to find the minimum distance from the origin.

However, as you mentioned, this problem can get quite complicated and may require some advanced mathematical techniques to solve. If you are struggling with it, I would recommend seeking help from a tutor or classmate who may have a better understanding of the Lagrange method. It's always a good idea to practice solving similar problems beforehand, so you can be better prepared for the test. Good luck!
 

1. What is the Lagrange Problem?

The Lagrange Problem is a mathematical optimization problem that aims to find the minimum distance from a given point (the origin) to a set of points. This problem was first introduced by mathematician Joseph-Louis Lagrange in the 18th century and has many real-world applications in fields such as physics, engineering, and economics.

2. Why is it called the "Crazy" Lagrange Problem?

The term "crazy" is often used to describe the Lagrange Problem because it involves finding the minimum distance from a point to a set of points, which can sometimes be a very complex and unpredictable process. This problem can also have multiple solutions, making it challenging and "crazy" to solve.

3. How is the Lagrange Problem solved?

The Lagrange Problem is typically solved using the method of Lagrange multipliers, which involves finding the critical points of a multivariable function subject to a set of constraints. This method allows us to find the minimum distance from the origin by setting up a system of equations and solving for the variables.

4. What are the real-world applications of the Lagrange Problem?

The Lagrange Problem has many practical applications, such as finding the shortest distance between two points in a map, minimizing the energy consumption of a system, and optimizing the path of a satellite orbiting a planet. It is also used in economics to find the best allocation of resources and in engineering to design efficient structures.

5. Are there any limitations to the Lagrange Problem?

Like any mathematical problem, the Lagrange Problem has its limitations. It can become computationally challenging when dealing with a large number of points or complex functions. Additionally, it may not always provide a unique solution, and the results may be sensitive to small changes in the input data. Therefore, it is essential to carefully consider the problem's assumptions and constraints before applying the Lagrange Problem to real-world situations.

Similar threads

Replies
9
Views
2K
  • Calculus and Beyond Homework Help
Replies
8
Views
468
Replies
9
Views
2K
Replies
1
Views
1K
Replies
3
Views
2K
  • Calculus and Beyond Homework Help
Replies
8
Views
1K
  • Advanced Physics Homework Help
Replies
7
Views
2K
  • Advanced Physics Homework Help
Replies
9
Views
1K
Back
Top