Multivariable Calculus: Finding the minimum and maximum value

You must have x= 0 or y= 0. In summary, The problem asks for the maximum and minimum values of the function f(x,y) = xy(x+2y-6) on a given region D, which is bounded by the hyperbola xy = 4 and the line x+2y-6 = 0. Using the Lagrange method, we find the critical points on the boundary of D to be (2,2) and (4,1). However, there is an additional critical point at (2√2,2/√2) that lies on the hyperbola but not the line. To find this point, we can use Lagrange multipliers with one
  • #1
theBEAST
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Homework Statement


Given f(x,y) = xy(x+2y-6), let D be the region in the plane between the hyperbola xy = 4 (let this be g) and the line x+2y-6 = 0 (let this be h). Find the maximum and minimum values of f(x,y) on D.

The Attempt at a Solution


I first found the critical points for f(x,y) and it turns out that none of them are in this region. Then I used lagrange to find the critical points on the boundary:
https://dl.dropbox.com/u/64325990/Photobook/Photo%202012-06-11%207%2026%2054%20PM.jpg

Solving this by hand and also confirming with wolfram I get the critical points (2,2) and (4,1). HOWEVER according to the answer key, there is one more critical point at (2√2,2/√2). They did this by solving the boundary case for xy=4 in between the regions 2 and 4 as shown here:
https://dl.dropbox.com/u/64325990/Capture.PNG

I am wondering why the Lagrange method I used did not give me (2√2,2/√2) as well?
 
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  • #2
You are using the Lagrange method that applies when you have two simultaneous constraints. So you are looking for the "critical points" that happen at the intersection of your hyperbola and your line.

You need to use Lagrange with one constraint at a time. Notice that the critical point you missed lies on the hyperbola but not the line. Or you could use substitution and reduce to a calc 1 problem, but that is up to you.
 
  • #3
In other words, you can use Lagrange multipliers to find max and min values on xy= 4, then use a different Lagrange multiplier calculation to find max and min values on x+ 2y- 6= 0.

Or, you could simply put the "conditions" into the function itself. On xy= 4, y= 4/x so f(x,y)= xy(x+ 2y- 6)= 4(x+ 4/x- 6). On x+ 2y- 6= 0, it is even easier: f(x,y)= xy(0)= 0 for all x.
 

1. What is multivariable calculus?

Multivariable calculus is a branch of mathematics that deals with functions of several variables. It extends the concepts of single variable calculus to functions with multiple independent variables.

2. How do you find the minimum and maximum value of a multivariable function?

To find the minimum and maximum value of a multivariable function, we use the method of partial derivatives. We take the partial derivative of the function with respect to each variable, set them equal to 0, and solve the resulting system of equations to find the critical points. Then, we evaluate the function at these critical points to determine the minimum and maximum values.

3. What is the significance of finding the minimum and maximum value of a function?

Finding the minimum and maximum value of a function is important because it allows us to optimize the function. For example, in economics, we can use the maximum and minimum values to determine the most profitable production level. In physics, we can use them to find the path of least resistance or maximum efficiency.

4. Can we apply the same methods of finding minimum and maximum values to all multivariable functions?

No, the method of finding minimum and maximum values through partial derivatives only works for differentiable functions. If a function is not differentiable, we may have to use other techniques such as the second derivative test or the method of Lagrange multipliers.

5. Are there any real-life applications of finding the minimum and maximum value of a multivariable function?

Yes, there are many real-life applications of finding the minimum and maximum value of a multivariable function. These include optimization problems in engineering, economics, physics, and computer science. For example, in engineering, we can use this method to optimize the design of a bridge or a building. In economics, we can use it to determine the most profitable pricing strategy for a product. In computer science, we can use it for optimizing algorithms and data structures.

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