Optimization, multivariable calculus

In summary, the problem involves finding the dimensions of an aquarium with a given volume that minimize the cost of materials, where the base is made of slate and the sides are made of glass. The cost of slate is five times that of glass per unit area. The approach involves finding the critical points of the cost function, which is the sum of the cost of the slate and the cost of the glass. Using the volume constraint, the cost function is reduced to two variables, and the partial derivatives are used to find the minimum.
  • #1
miglo
98
0

Homework Statement


the base of an aquarium with given volume V is made of slate and the sides are made of glass. if slate costs five times as much (per unit area) as glass, find the dimensions of the aquarium that minimize the cost of the materials.


Homework Equations





The Attempt at a Solution


so this problem fall under finding max, min and saddle points of a function
i think that lagrange multipliers can also be used but id like to first solve it by finding critical points and then the minimum
so first i know that V=xyz and and the total area of the glass will be 2xz+2yz while the area of the base slate will be xy
then the cost function will be C(x,y,z)=the cost of the slate + the cost of the glass
so then C(x,y,z)=5(2xz+2yz)+(2xz+2yz)= 12xz+12yz=z(12x+12y)(?)
im not really sure what to do next, but what i though of doing was to solve for z in V=xyz, then using that z by replacing it for the z in C(x,y,z) then i would only have a function of 2 variables C(x,y) and then i can just go ahead and find partial derivatives and use the second derivative test to find the minimum
is this the correct way to go about finding the dimensions?
 
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  • #2
miglo said:

Homework Statement


the base of an aquarium with given volume V is made of slate and the sides are made of glass. if slate costs five times as much (per unit area) as glass, find the dimensions of the aquarium that minimize the cost of the materials.


Homework Equations





The Attempt at a Solution


so this problem fall under finding max, min and saddle points of a function
i think that lagrange multipliers can also be used but id like to first solve it by finding critical points and then the minimum
so first i know that V=xyz and and the total area of the glass will be 2xz+2yz while the area of the base slate will be xy
then the cost function will be C(x,y,z)=the cost of the slate + the cost of the glass
so then C(x,y,z)=5(2xz+2yz)+(2xz+2yz)= 12xz+12yz=z(12x+12y)(?)
im not really sure what to do next, but what i though of doing was to solve for z in V=xyz, then using that z by replacing it for the z in C(x,y,z) then i would only have a function of 2 variables C(x,y) and then i can just go ahead and find partial derivatives and use the second derivative test to find the minimum
is this the correct way to go about finding the dimensions?

Try it and see! The only real way to learn is to go ahead and do it. (Note: an alternative would be to use a Lagrange multiplier method.)

RGV
 
  • #3
i actually did try right at after posting my question
heres what i got
C(x,y,z)=z(12x+12y)
solving for z in V=xyz gives me z=V/(xy)
then C(x,y)=V/(xy)(12x+12y)=12V/y+12V/x
C_x(partial derivative)=-12V/x^2 and C_y=-12V/y^2
this leads to a problem because then i have no critical points
any suggestions?
 
  • #4
miglo said:
i actually did try right at after posting my question
heres what i got
C(x,y,z)=z(12x+12y)
solving for z in V=xyz gives me z=V/(xy)
then C(x,y)=V/(xy)(12x+12y)=12V/y+12V/x
C_x(partial derivative)=-12V/x^2 and C_y=-12V/y^2
this leads to a problem because then i have no critical points
any suggestions?

You made a error writing down the cost. Cost = 2xz+2yz + 5xy [=cost of 2 sides + cost of 2 ends + cost of bottom---assuming no top]. When you use the volume constraint to eliminate z, you get an expression C(x,y) that does have a stationary point in x>0,y>0.

RGV
 
  • #5
ohh sweet thanks!
i left a question mark after writing down the cost function because i wasnt quite sure i had the right function for the cost
 

Related to Optimization, multivariable calculus

1. What is optimization in multivariable calculus?

Optimization in multivariable calculus is the process of finding the maximum or minimum value of a function with multiple variables. This involves taking partial derivatives and setting them equal to zero to find critical points, and then using the second derivative test to determine if the critical point is a maximum or minimum.

2. What is the difference between local and global optimization?

Local optimization involves finding the maximum or minimum value of a function within a specific region or interval. Global optimization, on the other hand, involves finding the maximum or minimum value of a function over its entire domain.

3. How is multivariable calculus used in optimization problems?

Multivariable calculus is used in optimization problems to find the optimal solution to a problem. This can be applied to various fields, such as engineering, economics, and physics, to optimize processes, maximize profits, or minimize costs.

4. What are some common optimization techniques used in multivariable calculus?

Some common optimization techniques in multivariable calculus include the gradient descent method, Lagrange multipliers, and the Newton-Raphson method. These techniques use the concepts of partial derivatives and second derivatives to find the optimal solution.

5. What are some real-life applications of multivariable calculus in optimization?

Multivariable calculus is used in a wide range of real-life applications, such as optimizing traffic flow, designing efficient structures, predicting weather patterns, and creating financial models. It is also used in machine learning and artificial intelligence algorithms to optimize processes and make predictions.

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