Max & Min Values of f(x,y) = x^2 + y^2 in Constraint 3x^2+4xy+6y^2=140

In summary, the book's solution for finding the maximum and minimum values of the function f(x,y) = x^2 + y^2 in the given constraint uses the Lagrange rule and takes partial derivatives for x, y and L. Then, by taking the coefficients determinant of the first two equations, the book finds values for L. However, the reason for using this method is not clear and may be related to Cramer's rule.
  • #1
magorium
9
0

Homework Statement



Show that , the maximum value of function f(x,y) = x^2 + y^2 is 70 and minimum value is 20
in constraint below.







Homework Equations



Constraint : 3x^2 + 4xy + 6y^2 = 140

The Attempt at a Solution



Book's solution simply states the Lagrange rule as :
h(x , y ; L) = x^2 + y^2 - L(3x^2 + 4xy + 6y^2 - 140)

Takes partial derivatives for x , y and L.


h's partial derivative for x = 2x + L(6x + 4y) = 0
h's partial derivative for y = 2y + L(4x + 12y) = 0
h's partial derivative for L = 3x^2 + 4xy + 6y^2 -140 = 0


Then he takes the coefficients determinant of first two equations ( h derv for x , h derv for y)

|1+3L 2L |
|2L 1+6L |

And makes this determinant equal to zero , finds values for L.




The part i don't understand is , why he uses Cramer rule to the first two equations and equals it to zero ?
 
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  • #2
magorium said:

Homework Statement



Show that , the maximum value of function f(x,y) = x^2 + y^2 is 70 and minimum value is 20
in constraint below.

Homework Equations



Constraint : 3x^2 + 4xy + 6y^2 = 140

The Attempt at a Solution



Book's solution simply states the Lagrange rule as :
h(x , y ; L) = x^2 + y^2 - L(3x^2 + 4xy + 6y^2 - 140)

Takes partial derivatives for x , y and L. h's partial derivative for x = 2x + L(6x + 4y) = 0
h's partial derivative for y = 2y + L(4x + 12y) = 0
h's partial derivative for L = 3x^2 + 4xy + 6y^2 -140 = 0 Then he takes the coefficients determinant of first two equations ( h derv for x , h derv for y)

|1+3L 2L |
|2L 1+6L |

And makes this determinant equal to zero , finds values for L.

The part i don't understand is , why he uses Cramer rule to the first two equations and equals it to zero ?

It is not clear to me that the book is using Cramer's rule, can you show more steps if it is indeed using Cramer's rule.

If they are not using Cramer's rule, then this is how I would interpret what is happening. From the first two equations, book want soutions to A[x y]=0, where [x y] is meant to be a column matrix, and A is a matrix depending on the value L.

We have the trivial solution x=y=0. To find a nontrivial solution, we note that would imply that det(A)=0. That gives us a polynomial in L to help us find candidate values for L, and continue solving equations with those candidates.EDIT: I just looked up Cramer's rule, it looks like you need determinant of A nonzero (else the denominator is zero), which is not something we need.
 
  • #3
magorium said:

Homework Statement



Show that , the maximum value of function f(x,y) = x^2 + y^2 is 70 and minimum value is 20
in constraint below.







Homework Equations



Constraint : 3x^2 + 4xy + 6y^2 = 140

The Attempt at a Solution



Book's solution simply states the Lagrange rule as :
h(x , y ; L) = x^2 + y^2 - L(3x^2 + 4xy + 6y^2 - 140)

Takes partial derivatives for x , y and L.


h's partial derivative for x = 2x + L(6x + 4y) = 0
h's partial derivative for y = 2y + L(4x + 12y) = 0
h's partial derivative for L = 3x^2 + 4xy + 6y^2 -140 = 0


Then he takes the coefficients determinant of first two equations ( h derv for x , h derv for y)

|1+3L 2L |
|2L 1+6L |

And makes this determinant equal to zero , finds values for L.




The part i don't understand is , why he uses Cramer rule to the first two equations and equals it to zero ?

Can x and y both = 0? If you agree they cannot both = 0 then you need to have a nonzero solution (x,y) of the linear equations
[tex] (6L+2) x + 4L y = 0\\
4L x + (12L+1) y = 0
[/tex]
What conditions do you need to satisfy in order that the solution is not x=y=0?

RGV
 
  • #4
magorium said:

Homework Statement



Show that , the maximum value of function f(x,y) = x^2 + y^2 is 70 and minimum value is 20
in constraint below.







Homework Equations



Constraint : 3x^2 + 4xy + 6y^2 = 140

The Attempt at a Solution



Book's solution simply states the Lagrange rule as :
h(x , y ; L) = x^2 + y^2 - L(3x^2 + 4xy + 6y^2 - 140)

Takes partial derivatives for x , y and L.


h's partial derivative for x = 2x + L(6x + 4y) = 0
h's partial derivative for y = 2y + L(4x + 12y) = 0
h's partial derivative for L = 3x^2 + 4xy + 6y^2 -140 = 0


Then he takes the coefficients determinant of first two equations ( h derv for x , h derv for y)

|1+3L 2L |
|2L 1+6L |

And makes this determinant equal to zero , finds values for L.




The part i don't understand is , why he uses Cramer rule to the first two equations and equals it to zero ?

In fact, I do not completely understand what you are asking, please clarify.
 
  • #5
algebrat you are right about that. Thanks for it. det(A)=0 actually comes from Cramer Rule for me. Since for finding the first unknown we use the special determinant for it divided by det(A) so since det(A) is 0 , that creates a uncertainty which avoids us finding a trivial solution. That's how i remember the det(A)=0 thing so that's possibly why i called it Cramer Rule :) Thanks for it.
 

Related to Max & Min Values of f(x,y) = x^2 + y^2 in Constraint 3x^2+4xy+6y^2=140

1. What is the maximum value of f(x,y) in the given constraint?

The maximum value of f(x,y) can be found by maximizing the objective function x^2 + y^2 while satisfying the constraint 3x^2+4xy+6y^2=140. This can be done using the method of Lagrange multipliers or by solving the system of equations formed by setting the partial derivatives of the objective function and the constraint equal to each other.

2. What is the minimum value of f(x,y) in the given constraint?

The minimum value of f(x,y) can be found by minimizing the objective function x^2 + y^2 while satisfying the constraint 3x^2+4xy+6y^2=140. This can also be done using the method of Lagrange multipliers or by solving the system of equations formed by setting the partial derivatives of the objective function and the constraint equal to each other.

3. How can the maximum and minimum values of f(x,y) be determined graphically?

The maximum and minimum values of f(x,y) can be determined graphically by plotting the contour lines of the objective function x^2 + y^2 and the constraint 3x^2+4xy+6y^2=140 on the same graph. The point where the contour lines intersect represents the maximum value and the point where the contour lines are closest to each other represents the minimum value.

4. Can the maximum and minimum values of f(x,y) be the same in the given constraint?

Yes, it is possible for the maximum and minimum values of f(x,y) to be the same in the given constraint. This can happen when the objective function and the constraint are parallel and the constraint is a tangent to the contour line of the objective function at that point.

5. How can the maximum and minimum values of f(x,y) be used in real-world applications?

The maximum and minimum values of f(x,y) can be used in many real-world applications, such as optimizing production levels in a manufacturing process, determining the most efficient route for a delivery, or finding the optimal location for a new business. In these scenarios, the objective function represents the desired outcome and the constraint represents the limitations or constraints that must be considered. By finding the maximum or minimum values, the most optimal solution can be determined.

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