Lagrange multiplier problem - function of two variables with one constraint

In summary, the conversation discusses finding the maximum and minimum values of a given function on a defined circle using Lagrange's method. The process involves finding the critical points by setting the partial derivatives of the function equal to the partial derivatives of the circle and solving the resulting system of equations.
  • #1
abery
2
0

Homework Statement


Find the maximum and minimum values of f(x,y) = 2x^2+4y^2 - 4xy -4x
on the circle defined by x^2+y^2 = 16.


Homework Equations


Lagrange's method, where f_x = lambda*g_x, f_y= lambda*g_y (where f is the given function and g(x,y) is the circle on which we are looking for the extrema)


The Attempt at a Solution


Computed the partials, and was able to end up with an equation like 2y -2 = [itex]\lambda[/itex]*(x-y)

From this, critical points look like they might be (1, root 15) and (root 15, 1) but this does not seem to be the answer.

Any help at all is much appreciated!
 
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  • #2
Well, it would have helped if you had show precisely what you did, not just generalities. "end up with an equation like 2y -2 = λ *(x-y)". Actually, I think you have f and g reversed but it really doesn't matter whether you use [itex]f_x= \lambda g_x[/itex] or [itex]g_x=(1/\lambda) f_x[/itex]

[itex]f(x,y)= 2x^2+ 4y^2- 4xy- 4x[/itex] and [itex]g(x,y)= x^2+ y^2= 16[/itex].
so [itex]f_x= 4x- 4y- 4[/itex] and [itex]g_x= 2x[/itex]. Your first equation is [itex]4x- 4y- 4= 2\lambda x[/itex]. [itex]f_y= 8y- 4x[/itex] and [itex]g_y= 2y[/itex]. Your second equation is [itex]8y- 4x= 2\lambda y[/itex]. Those, together with the condition that [itex]x^2+ y^2= 16[/itex], give you three equations to solve for x, y, and [itex]\lambda[/itex].

But the value of [itex]\lambda[/itex] is not really necessary to solve this problem and I find that it is often best to eliminate [itex]\lambda[/itex] from the first two equations by dividing one by the other.
 
  • #3
Thanks for your help, HallsOfIvy. My problem is with solving the resulting system of equations. (Thanks for the suggestion to divide the equations)

After doing that and rearranging the first two, I get: x2 - xy -y2 - y =0

And using the third (original) constraint, I get -2y2 - xy - y - 16 = 0, but am not sure how to proceed.


HallsofIvy said:
Well, it would have helped if you had show precisely what you did, not just generalities. "end up with an equation like 2y -2 = λ *(x-y)". Actually, I think you have f and g reversed but it really doesn't matter whether you use [itex]f_x= \lambda g_x[/itex] or [itex]g_x=(1/\lambda) f_x[/itex]

[itex]f(x,y)= 2x^2+ 4y^2- 4xy- 4x[/itex] and [itex]g(x,y)= x^2+ y^2= 16[/itex].
so [itex]f_x= 4x- 4y- 4[/itex] and [itex]g_x= 2x[/itex]. Your first equation is [itex]4x- 4y- 4= 2\lambda x[/itex]. [itex]f_y= 8y- 4x[/itex] and [itex]g_y= 2y[/itex]. Your second equation is [itex]8y- 4x= 2\lambda y[/itex]. Those, together with the condition that [itex]x^2+ y^2= 16[/itex], give you three equations to solve for x, y, and [itex]\lambda[/itex].

But the value of [itex]\lambda[/itex] is not really necessary to solve this problem and I find that it is often best to eliminate [itex]\lambda[/itex] from the first two equations by dividing one by the other.
 

1. What is the Lagrange multiplier method?

The Lagrange multiplier method is a mathematical technique used to find the extrema (maximum or minimum) of a function of two variables subject to a single constraint. It involves creating a new function, called the Lagrangian, by adding a multiple of the constraint function to the original function. This new function is then used to find the extrema by setting its partial derivatives equal to zero.

2. How is the Lagrange multiplier method used to solve optimization problems?

The Lagrange multiplier method is used to solve optimization problems by finding the critical points of the Lagrangian function. These critical points correspond to the extrema of the original function subject to the constraint. By solving the system of equations formed by setting the partial derivatives of the Lagrangian equal to zero, the values of the variables at the extrema can be found.

3. What is the significance of the constraint in the Lagrange multiplier method?

The constraint in the Lagrange multiplier method plays a crucial role in determining the extrema of the function. It restricts the domain of the original function and ensures that the critical points found using the Lagrangian function satisfy the constraint. Without the constraint, the critical points may not necessarily be the extrema of the original function.

4. Can the Lagrange multiplier method be used for functions with multiple constraints?

Yes, the Lagrange multiplier method can be extended to functions with multiple constraints. In this case, the Lagrangian function would include a multiple of each constraint function, and the system of equations formed by setting its partial derivatives equal to zero would have multiple variables and Lagrange multipliers to be solved for.

5. What are some real-world applications of the Lagrange multiplier method?

The Lagrange multiplier method has various real-world applications, such as in economics, physics, and engineering. It can be used to optimize production processes, maximize profit or utility, and minimize energy consumption. It is also used in the field of mechanics to find the path of least resistance for a moving object subject to constraints.

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