Determine the minimum using the second derivative

In summary, the speaker is trying to determine the minimum dimensions of a 1 cubic foot box without a top. They are attempting to minimize the surface area by taking the derivative of the area equation and using the second derivative to ensure it is a minimum. They are unsure of how to proceed with two variables and partial derivatives. They also mention the possibility of assuming that length and width are equal to simplify the problem.
  • #1
ranger1716
18
0
I was wondering if someone could show me where to go next in this problem.

I need to determine the minimum length, width and height that a 1 cubic foot box can have. This box does not have a top. I know that I need to minimize the area, but I'm not sure if I'm going about this correctly. So far I have that A(l,w)=lw+2(1/l)+2(1/w). I made the substitution from three to two variables because V=lwh therefore h=1/lw.

I'm assuming that I need to take the derivative of the area equation, and then determine the minimum using the second derivative. Is this the correct procedure?

Thanks!
 
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  • #2
You need to take the derivative of the area equation and find where it's 0. Then you can check with the second derivative to ensure that that point is a minimum.
 
  • #3
0rthodontist said:
You need to take the derivative of the area equation and find where it's 0. Then you can check with the second derivative to ensure that that point is a minimum.

That's what I was thinking, however I don't know how to do this with two variables. I'm in Calc 3 but we haven't yet done partial derivatives. Everything that I have seen (including using Maple) needs to use partial derivatives to solve the problem. I've basically attempted to take the derivative using Maple, and got a partial derivative. I don't really know where to continue on to.
 
Last edited:
  • #4
Oh, right, you do need partial derivatives, using the Hessian. On the other hand you could make the assumption l = w, which you could prove--start by saying that if l > w (without loss of generality) then there is a cheaper box with the same volume and height where l = w.
 

1. What is the second derivative test for determining the minimum of a function?

The second derivative test is a mathematical method for identifying the minimum point of a function. It involves taking the second derivative of a function at a certain point and analyzing its sign to determine whether that point is a minimum or maximum.

2. How does the second derivative test work?

The second derivative test works by taking the second derivative of a function, which represents the rate of change of the function's slope. If the second derivative is positive at a certain point, it means that the slope of the function is increasing and the point is a minimum. If the second derivative is negative, it means that the slope is decreasing and the point is a maximum.

3. What is the importance of using the second derivative to determine the minimum of a function?

Using the second derivative is important because it provides a more accurate and efficient way of finding the minimum point of a function. It allows us to analyze the curvature of the function at a specific point, which can provide valuable information for optimization problems in various fields such as economics, physics, and engineering.

4. Are there any limitations to using the second derivative test?

Yes, there are some limitations to using the second derivative test. It can only be applied to functions that are twice differentiable, meaning their first and second derivatives exist and are continuous. Additionally, it can only identify local minima, not global minima, and it may not work for certain types of functions such as those with inflection points.

5. Can the second derivative test be used to find the maximum of a function?

Yes, the second derivative test can also be used to find the maximum of a function. However, it is important to note that the test only identifies local maximum points, so it may not give the global maximum of a function. Also, the sign of the second derivative at a maximum point will be negative instead of positive as it is for a minimum point.

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