Lagrange Multipliers Problem

In summary: The portions to be considered in the problem are the lateral surface of the frustum, and the upper and lower bases.Thanks.Your problem is minimizing the surface area of a conical frustum w.r.t a given volume. The surface area and volume of the frustum are$$A=\pi (r_b + r_f)\sqrt{h^2+(r_b - r_f)^2}\\V=\frac{\pi h}{3}(r_b^2+r_br_f+r_f^2)$$where ##r_b## is the radius of the base, ##r_f## is the radius of the
  • #1
Morfe
6
1
Hi there!
Kindly help me to solve the problem below.

A company is using frustum of a cone containers for their products. What are the dimensions of the least expensive container that can hold 300 cubic cm? Use Lagrange Multipliers to solve the problem.

Thanks.
 
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  • #2
Well, what do you know already to set up this exercise ?
 
  • #3
Morfe said:
Hi there!
Kindly help me to solve the problem below.

A company is using frustum of a cone containers for their products. What are the dimensions of the least expensive container that can hold 300 cubic cm? Use Lagrange Multipliers to solve the problem.

Thanks.
Well, to do Lagrange multipliers you need two things, first of all, some functions that you want to minimize, in your case is only one function, the cost, so find a function that gives you the cost of any frustum of a cone.
Then you also need a set of function to constrain, in your case again is only one, that is the volume, so you also need to find a function that gives you the volume of any frustum.

Try to find these two functions first before continue.
 
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  • #4
Gaussian97 said:
Well, to do Lagrange multipliers you need two things, first of all, some functions that you want to minimize, in your case is only one function, the cost, so find a function that gives you the cost of any frustum of a cone.
Then you also need a set of function to constrain, in your case again is only one, that is the volume, so you also need to find a function that gives you the volume of any frustum.

Try to find these two functions first before continue.
Hi I already generated the system of equations from the partial derivatives (please see attachment). My problem now is on how to compute the system of equation with complex equations. Thanks. Hope you can help me with this.
 

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  • #5
I see three unknowns (##H, h, k##) (*). So I expect three equations. Are there pages missing :wink: ?

(*) Well, you make things difficult by bringing ##L## into the expressions. But it's not a new unknown.
 
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  • #6
BvU said:
I see three unknowns (##H, h, k##). So I expect three equations. Are there pages missing :wink: ?
There are four variables (H,h,k,λ) and I was able to generate four equations. The four equations are on the attachment. Thanks.:smile:
 
  • #7
Oops, more pages! My bad.
So what's the problem :rolleyes: ?
 
  • #8
BvU said:
Oops, more pages! My bad.
So what's the problem :rolleyes: ?
My problem now is on how to compute the system of equation with complex equations.
Thanks for the help.
 
  • #9
Morfe said:
My problem now is on how to compute the system of equation with complex equations.
Thanks for the help.
Is it possible to solve the system of equation found on the attachment? Or are there any software that can solve it?
Thanks.
 
  • #10
Try to add the equation (1) and (2)
 
  • #11
The problem is not stated clearly enough to be solved.

Exactly which part(s) of the frustum of a cone need to be manufactured? Is it just the portion of the cone per se? The cone and the larger disk? The cone and the smaller disk? The cone and both disks?

And presumably the cost is proportional to the total surface area.

These things need to clarified before charging ahead blindly to solve the problem, since it's always useful to know which problem you want to be solving.
 
  • #12
zinq said:
The problem is not stated clearly enough to be solved.

Exactly which part(s) of the frustum of a cone need to be manufactured? Is it just the portion of the cone per se? The cone and the larger disk? The cone and the smaller disk? The cone and both disks?

And presumably the cost is proportional to the total surface area.

These things need to clarified before charging ahead blindly to solve the problem, since it's always useful to know which problem you want to be solving.

Hi!
The portions to be considered in the problem are the lateral surface of the frustum, and the upper and lower bases.
Thanks.
 
  • #13
Your problem is minimizing the surface area of a conical frustum w.r.t a given volume. The surface area and volume of the frustum are$$
A=\pi (r_b + r_f)\sqrt{h^2+(r_b - r_f)^2}\\
V=\frac{\pi h}{3}(r_b^2+r_br_f+r_f^2)$$where ##r_b## is the radius of the base, ##r_f## is the radius of the frustum and ##h## is the height. If you use the Lagrangian multiplier method your Lagrangian is$$
\mathcal {L}(r_b,r_f,h,\lambda) = \pi (r_b + r_f)\sqrt{h^2+(r_b - r_f)^2} +\lambda (\frac{\pi h}{3}(r_b^2+r_br_f+r_f^2)-\gamma)$$ where ##\gamma## is the constraining volume and ##\lambda## is the Lagrangian multiplier. We get four equations in four unknowns:$$
\frac{\partial {\mathcal {L}(r_b,r_f,h,\lambda)}}{\partial {r_b}}=0\\
\frac{\partial {\mathcal {L}(r_b,r_f,h,\lambda)}}{\partial {r_f}}=0\\
\frac{\partial {\mathcal {L}(r_b,r_f,h,\lambda)}}{\partial {h}}=0\\
\frac{\partial {\mathcal {L}(r_b,r_f,h,\lambda)}}{\partial {\lambda}}=0$$
On performing these derivatives and eliminating variables one is quickly confronted with an intractable problem in algebra. I therefore propose that minimizing the perimeter of the frustum cross section w.r.t. area is, by rotational symmetry, equivalent to minimizing the surface area w.r.t. volume. The minimal perimeter of a rectangle is a square and the minimal perimeter of a right triangle is a ##\frac{\pi}{4}## equilateral triangle. Let ##x## be the side of a square. We find:$$
r_b=\frac{3}{2}x\\
r_f=\frac{1}{2}x\\
h=x$$and solving for x w.r.t to volume$$
\gamma = \frac{\pi}{3}x^2(\frac{9}{4}+\frac{3}{4} +\frac{1}{4})\\
x=\sqrt{\frac{12\gamma}{13\pi}}$$Using the Lagrangian multiplier method to solve this problem is like using a bulldozer to do the job of a garden trowel.
 

1. What is the Lagrange Multipliers Problem?

The Lagrange Multipliers Problem is a mathematical optimization problem that involves finding the maximum or minimum value of a function subject to certain constraints. It was developed by mathematician Joseph-Louis Lagrange in the late 18th century and has applications in various fields such as physics, economics, and engineering.

2. How does the Lagrange Multipliers method work?

The Lagrange Multipliers method involves creating a new function, called the Lagrangian, which combines the original function and the constraint equations using a set of multipliers. The critical points of the Lagrangian function, where the partial derivatives are equal to zero, correspond to the maximum or minimum values of the original function subject to the given constraints.

3. What are the advantages of using Lagrange Multipliers?

The Lagrange Multipliers method allows for the optimization of a function subject to multiple constraints, which may be difficult or impossible to solve using other methods. It also provides a systematic approach to solving constrained optimization problems and can be applied to both continuous and discrete functions.

4. What are some common applications of the Lagrange Multipliers Problem?

The Lagrange Multipliers Problem has various applications in physics, economics, and engineering. It is commonly used in mechanics to find the minimum energy state of a system, in economics to optimize production or consumption levels, and in engineering to design structures that can withstand external forces while minimizing material usage.

5. What are some limitations of the Lagrange Multipliers method?

One limitation of the Lagrange Multipliers method is that it may not always provide the global maximum or minimum of a function, only the local extremum. It also requires the function and constraints to be differentiable, which may not always be the case in real-world problems. Additionally, the method can become computationally expensive for problems with a large number of constraints.

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