Lagrange Multiplier question with solid attempt

In summary: Since specific values of \lambda are not part of the "solution" of problems like these, I find it is often a good step to start by dividing one equation by another, eliminating \lambda at the start. Here, your equations are 1= 4\lambda x and 2y= 2\lambda y[/i2tex]. Dividing the second equation by the first:\frac{2y}{1}= \frac{2\lambda y}{\lambda x}= \frac{2y}{x}which reduces to x= 1 or y= 0.However, you say your constraint is "g(x,y)= 2x^2+ y^2- 1" which
  • #1
tamintl
74
0

Homework Statement



Use the method of Lagrange multipliers to find the maximum and minimum values of the function

f(x, y) = x + y2

subject to the constraint g(x,y) = 2x2 + y2 - 1


Homework Equations



none

The Attempt at a Solution



We need to find [itex]\nabla[/itex]f = λ[itex]\nabla[/itex]g

Hence,

[itex]\nabla[/itex]fx - λ[itex]\nabla[/itex]gx = 0

Which becomes, 1 - λ(4x) = 0

[itex]\nabla[/itex]fy - λ[itex]\nabla[/itex]gy = 0

Which becomes, 2y - λ = 0

-------------------------

Now we have: x = 1/4λ and y = λ/2

I assume I am right in now subbing x and y into the constraint...

To give us: 2/16λ2 + λ2/4 - 1 = 0


It seems a bit messy considering this is an elementary part of my homework? Have I gone wrong somewhere?

Regards as always
 
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  • #2
Your [itex] \partial{L}/\partial{y}[/itex] is incorrect; try again.

RGV
 
  • #3
Ray Vickson said:
Your [itex] \partial{L}/\partial{y}[/itex] is incorrect; try again.

RGV

Wow, rookie error..

yep dL/dy = 2y - λ(2y)
so λ = 1

Thus, x=1/4

Put this into constraint to get: y=7/8

So (1/4,7/8) is a point..

How do i find the maximum and minimum? thanks
 
  • #4
the equation 2y = lambda*(2y) has TWO solutions: lambda = 1 is one of them. Can you see another?

RGV
 
  • #5
Since specific values of [itex]\lambda[/itex] are not part of the "solution" of problems like these, I find it is often a good step to start by dividing one equation by another, eliminating [itex]\lambda[/itex] at the start. Here, your equations are [itex]1= 4\lambda x[/itex] and [itex]2y= 2\lambda y[/i2tex]. Dividing the second equation by the first:
[tex]\frac{2y}{1}= \frac{2\lambda y}{\lambda x}= \frac{2y}{x}[/tex]
which reduces to x= 1 or y= 0.

However, you say your constraint is "[itex]g(x,y)= 2x^2+ y^2- 1[/itex]" which is not a constraint at all. Did you mean [itex]g(x,y)= 2x^2+ y^2= 1[/itex]? If so, set x= 1 in that and solve for y, then set y= 0 and solve for x.
 
  • #6
The statement that "specific values of lambda are not part of the solution ..." is either misleading or wrong, depending on exactly how you meant it. ONE of the max or min points IS obtained by looking at lambda = 1 and seeing the consequences.

RGV
 

Related to Lagrange Multiplier question with solid attempt

1. What is the purpose of using Lagrange multipliers in optimization problems?

The purpose of using Lagrange multipliers is to find the maximum or minimum value of a function subject to constraints. It allows us to incorporate constraints into the objective function and solve for optimal values.

2. How does the Lagrange multiplier method work?

The Lagrange multiplier method involves creating a new function, called the Lagrangian, which combines the original objective function and the constraints. The optimal solution is then found by setting the gradient of the Lagrangian equal to zero and solving the resulting equations.

3. What is a solid approach for solving a Lagrange multiplier question?

A solid approach for solving a Lagrange multiplier question involves identifying the objective function and constraints, setting up the Lagrangian, taking the partial derivatives of the Lagrangian, and solving the resulting equations simultaneously to find the optimal values for the variables.

4. Can the Lagrange multiplier method be used for both single and multi-variable optimization problems?

Yes, the Lagrange multiplier method can be used for both single and multi-variable optimization problems. In single-variable problems, there is only one constraint and one Lagrange multiplier. In multi-variable problems, there are multiple constraints and multiple Lagrange multipliers.

5. What are some common applications of the Lagrange multiplier method?

The Lagrange multiplier method is commonly used in economics, physics, engineering, and other fields to optimize functions subject to constraints. It is also used in machine learning and statistics for parameter estimation and model selection.

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