Lagrange multipliers: help solving for x, y and lambda

In summary: Homework Statement Find the local extreme values of ƒ(x, y) = x2y on the line x + y = 3Homework Equations∇ƒ = λ∇gThe Attempt at a Solution2yxi+x^2j = λi + λj[2yx=λ] [x^2=λ] [x+y=3][2yx=x^2] & [(2y)+y=3][2y
  • #1
rudy
45
9

Homework Statement


Find the local extreme values of ƒ(x, y) = x2y on the line x + y = 3

Homework Equations


∇ƒ = λ∇g

The Attempt at a Solution


2yxi+x^2j = λi + λj
[2yx=λ] [x^2=λ] [x+y=3]
[2yx=x^2] & [(2y)+y=3]
[2y=x] & [y=1]
x=2

This is as far as I got, and gives f(2,1)=4 as the extreme value. The solution I have (chegg.com) lists another possible solution.

On the left column, they give another solution to the equation 2y=x:
They say:
2y=x
x=0
and proceed to use the "x+y=3" equation to give an alternative extrema which is f(0,3)

Can anyone explain how they made the jump from 2y=x to x=0?
Why isn't y=0 another solution? (If x equals and 2y equals x, then y must equal zero)

Thanks in advance, screenshot from solution below

-Rudy

Screen Shot 2018-07-22 at 8.55.24 PM.png
 

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  • #2
rudy said:

Homework Statement


Find the local extreme values of ƒ(x, y) = x2y on the line x + y = 3

Homework Equations


∇ƒ = λ∇g

The Attempt at a Solution


2yxi+x^2j = λi + λj
[2yx=λ] [x^2=λ] [x+y=3]
[2yx=x^2] & [(2y)+y=3]
[2y=x] & [y=1]
x=2

This is as far as I got, and gives f(2,1)=4 as the extreme value. The solution I have (chegg.com) lists another possible solution.

On the left column, they give another solution to the equation 2y=x:
They say:
2y=x
x=0
and proceed to use the "x+y=3" equation to give an alternative extrema which is f(0,3)

Can anyone explain how they made the jump from 2y=x to x=0?
Why isn't y=0 another solution? (If x equals and 2y equals x, then y must equal zero)

Thanks in advance, screenshot from solution below

-Rudy

View attachment 228274
You ignored the second solution when you reduced ##2xy = x^2## to ##2y=x##. Try writing it as ##2xy-x^2=0## and factoring it.
 
  • #3
rudy said:

Homework Statement


Find the local extreme values of ƒ(x, y) = x2y on the line x + y = 3

Homework Equations


∇ƒ = λ∇g

The Attempt at a Solution


2yxi+x^2j = λi + λj
[2yx=λ] [x^2=λ] [x+y=3]
[2yx=x^2] & [(2y)+y=3]
[2y=x] & [y=1]
x=2

This is as far as I got, and gives f(2,1)=4 as the extreme value. The solution I have (chegg.com) lists another possible solution.

On the left column, they give another solution to the equation 2y=x:
They say:
2y=x
x=0
and proceed to use the "x+y=3" equation to give an alternative extrema which is f(0,3)

Can anyone explain how they made the jump from 2y=x to x=0?
Why isn't y=0 another solution? (If x equals and 2y equals x, then y must equal zero)

Thanks in advance, screenshot from solution below

-Rudy

View attachment 228274

I think their writeup was bad. It should have said "##2xy = x^2 \Rightarrow x = 0 \; {\bf \text{or}} \; 2y = x##."
 

FAQ: Lagrange multipliers: help solving for x, y and lambda

What is the purpose of using Lagrange multipliers?

The purpose of using Lagrange multipliers is to find the maximum or minimum value of a function subject to one or more constraints. It allows for the optimization of a function while satisfying certain constraints.

How do I solve for x, y, and lambda using Lagrange multipliers?

To solve for x, y, and lambda using Lagrange multipliers, you must first set up the Lagrangian function by adding the product of the constraints and their corresponding Lagrange multipliers to the original function. Then, take the partial derivatives of the Lagrangian with respect to x, y, and lambda and set them equal to 0. Finally, solve the resulting system of equations to find the values of x, y, and lambda.

What is the geometric interpretation of Lagrange multipliers?

The geometric interpretation of Lagrange multipliers is that the maximum or minimum of a function subject to constraints occurs when the gradient of the function is parallel to the gradient of the constraint. This can be visualized as the function and constraint curves touching at a single point.

How do I know if my solution using Lagrange multipliers is a maximum, minimum, or saddle point?

To determine if your solution is a maximum, minimum, or saddle point, you must calculate the second derivatives of the Lagrangian function with respect to x and y. If the second derivative with respect to both x and y is positive, the solution is a minimum. If it is negative, the solution is a maximum. If it is mixed, the solution is a saddle point.

Can Lagrange multipliers be used for non-linear constraints?

Yes, Lagrange multipliers can be used for non-linear constraints. The process for solving for x, y, and lambda is the same as for linear constraints, but the resulting system of equations may be more complex and require numerical methods to solve.

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