Lagrange Multiplier Problem

In summary: The same argument eliminates y=0 as a possibility. So you are left with the system of equations ##2x-2y=2\lambda x,\ 4y-2x=2\lambda y,\ x^2+y^2-1=0,\ x\ne 0,\ y\ne 0##.
  • #1
MrCreamer
6
0

Homework Statement



Find the extrema of f(x, y) = x2−2xy+ 2y2, subject to the
constraint x2 +y2 = 1.

Homework Equations



∇f(x,y) = λg(x,y)

The Attempt at a Solution



This is the work I have thus far:

Letting g(x,y) = x2+y2-1,

We obtain the following three equations from the Lagrange Multiplier equation:

2x-2y = 2λx
4y-2x = 2λy
x2+y2-1=0

I know that x and y cannot both be zero due to the constraint equation.

If x = 0:

4y = 2λy

--> λ = 2

If y = 0:

2x = 2λx

--> λ = 1

I have no idea what else to do
 
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  • #2
MrCreamer said:

Homework Statement



Find the extrema of f(x, y) = x2−2xy+ 2y2, subject to the
constraint x2 +y2 = 1.


Homework Equations



∇f(x,y) = λg(x,y)


The Attempt at a Solution



This is the work I have thus far:

Letting g(x,y) = x2+y2-1,

We obtain the following three equations from the Lagrange Multiplier equation:

2x-2y = 2λx
4y-2x = 2λy
x2+y2-1=0

I know that x and y cannot both be zero due to the constraint equation.

If x = 0:

4y = 2λy

--> λ = 2

If y = 0:

2x = 2λx

--> λ = 1

I have no idea what else to do

Using the symbol u instead of λ, you have:
##(1-u)x = y## and ##(2-u)y = x##, so ##0 = x(u^2 - 3u + 1)##.
 
  • #3
MrCreamer said:
We obtain the following three equations from the Lagrange Multiplier equation:

2x-2y = 2λx
4y-2x = 2λy
x2+y2-1=0

I know that x and y cannot both be zero due to the constraint equation.

If x = 0:

4y = 2λy

--> λ = 2

If y = 0:

2x = 2λx

--> λ = 1

I have no idea what else to do
At this point, there's really no reason to consider the cases x=0 and y=0. Nothing in the equations obviously suggests that either of those cases have anything to do with solving the system of equations. However, after you combine the equations the way Ray suggests, you find x=0 could be part of a possible solution. You found this implies that ##y \ne 0## and ##\lambda=2##. The first equation, however, then requires that ##y=0##, which is a contradiction. You can therefore eliminate x=0 as a possibility.
 

1. What is the Lagrange Multiplier Problem?

The Lagrange Multiplier Problem is a method used in calculus to find the maximum or minimum values of a function, subject to certain constraints. It involves using a Lagrange multiplier, which is a constant that helps incorporate the constraints into the objective function.

2. When is the Lagrange Multiplier Problem used?

The Lagrange Multiplier Problem is often used in optimization problems where the objective function is subject to one or more constraints. It is also commonly used in economics and physics to find optimal solutions to problems with constraints.

3. How is the Lagrange Multiplier calculated?

To solve the Lagrange Multiplier Problem, the objective function and constraints are first written in a specific form. Then, the Lagrange multiplier is calculated by taking the partial derivatives of the objective function and setting them equal to the partial derivatives of the constraints multiplied by the Lagrange multiplier. This system of equations is then solved to find the optimal values for both the objective function and the multiplier.

4. What are some applications of the Lagrange Multiplier Problem?

The Lagrange Multiplier Problem has many applications in various fields, including economics, physics, engineering, and statistics. For example, it can be used to find the optimal production levels for a company with limited resources, or to calculate the shortest distance between two points on a surface. It is also commonly used in regression analysis to find the best-fitting line for a set of data points.

5. Are there any limitations to the Lagrange Multiplier Problem?

While the Lagrange Multiplier Problem is a powerful tool for solving optimization problems, it does have some limitations. It can only be used for problems with a single constraint or a set of independent constraints. Additionally, it may not always find the global maximum or minimum of a function, and multiple solutions may exist for certain problems.

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