Best dimensions for maximum surface area

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SUMMARY

The discussion centers on maximizing the volume of a rectangular box given a fixed surface area of 400 cm². The two primary methods outlined for solving this problem are: first, reducing the number of variables using the surface area constraint and then differentiating the resulting volume function; second, employing the Lagrange Multiplier method to find the maximum volume. Both approaches ultimately reveal that the optimal dimensions occur when the box is a cube, confirming that equal dimensions (x = y = z) yield the maximum volume for a given surface area.

PREREQUISITES
  • Understanding of calculus, specifically differentiation and partial derivatives
  • Familiarity with the concept of Lagrange Multipliers
  • Knowledge of surface area and volume formulas for three-dimensional shapes
  • Basic graphing skills for visualizing functions
NEXT STEPS
  • Study the application of Lagrange Multipliers in optimization problems
  • Learn how to differentiate functions of multiple variables
  • Explore the geometric interpretation of surface area and volume relationships
  • Investigate other optimization techniques in calculus, such as the method of substitution
USEFUL FOR

Mathematicians, engineering students, and anyone involved in optimization problems related to geometry and calculus.

bjgawp
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I was doing some math problems involving surface area and maximum dimensions and then I wondered:
Suppose you are given the surface area of a rectangular box but none of its dimensions. Is it possible to find the best dimensions (x,y,z) that would give the maximum volume of the box? I was thinking of something along the lines of making a graph and finding its maximum value ... Ex. 400cm² = 2xy + 2xz + 2yz. Possible? Unless there are other ways of doing it...
 
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Make a graph of what? Not the surface area function that you give: you want to maximize the volume: V= xyz.

The standard way of "maximizing" (or "minimizing") a function is to find its derivative and set that equal to 0. Since here you have a function of three variables (x,y,z) and an additional constraint, there are two ways to do it.

1) Use the constraint to reduce the number of variables: 2xy+ 2xz+ 2yz= 400 so 2(x+y)z= 400- 2xy so z= (200-xy)/(x+y) and then V= xy(200-xy)/(x+y). Differentiate that with respect to x and y (partial derivatives) and set them equal to 0. You can probably see those are going to be messy derivatives!

2) The Lagrange Multiplier method: At a maximum (or minimum) value, the gradient of the function must be a multiple of the gradient of the constraint. Here the function to be maximized is V= xyz. grad V= yzi+ xzj+ xyk. The constraint function is U= 2xy+ 2xz+ 2yz= 400 and grad U= (2y+ 2z)i+ (2x+2z)j+ (2x+2y)k. One is a multiple of the other if yz= \lambda(2y+ 2z), xz= \lamba(2x+2z), and xy= \lambda(2x+ 2y). That \lambda is the "Lagrange Multiplier".
If you eliminate \lambda from those, you can get immediately that x= y= z: a cube will maximize volume for given surface area.
 
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