Optimazation math homework

In summary, the conversation discusses finding the dimensions of a rectangular box with the greatest volume that can be constructed from 100 square inches of cardboard, with the base being twice as long as it is wide. The individual attempted to solve the problem using an equation, but may have made a mistake. The conversation then provides two methods for finding the maximum volume, either by solving for y in a constraint equation or using a lagrange multiplier.
  • #1
jenjen07
4
0
I'm lost with this problem. If anyone can help at all I'd really appreciate it.

What are the dimensions of the base of the rectangular box of greatest volume that can be constucted from 100 suqare inches of cardboard if the base is to be twice as long as it is wide? Assume that the box has a top.

I tried it and I got my voume to equal 100x^2-4x^4 divided by 3x. Maybe I have the equation wrong. Thanks for your help.

Jen
 
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  • #2
the sides of the bottom of the box are x and 2x, and the height is y, so you want to maximize the volume:

[tex] V= 2x^2 y [/tex]

with the constraint that the surface area is 100:

[tex] 4x^2 + 2x y + 4 x y = 100[/tex]

You could solve for y in the constraint equation, plug that in for the volume and maximize, or you could use a lagrange multiplier.
 
  • #3


Hi Jen,

I can definitely help you with this problem. First, let's start by breaking down the information given in the problem. We know that we have 100 square inches of cardboard to work with and that the base of the box is twice as long as it is wide. So, we can represent the base as 2x by x (length by width). We also know that the box has a top, which means we need to account for the height of the box as well. Let's represent the height as h.

To find the volume of the box, we use the formula V = lwh. In this case, our length is 2x, our width is x, and our height is h. So, our equation becomes V = 2x * x * h, which simplifies to V = 2x^2 * h.

Now, we have to take into account the constraint that we have 100 square inches of cardboard to work with. The surface area of a rectangular box is given by SA = 2lw + 2lh + 2wh. Since we have a top, we can ignore the top and only focus on the sides. So, our equation becomes 100 = 2(2x)(x) + 2(2x)(h) + 2(x)(h). Simplifying this, we get 100 = 4x^2 + 4xh + 2xh.

Now, we can use this equation to solve for h in terms of x. First, let's factor out an h from the right side of the equation. This gives us 100 = 4x^2 + (4x + 2)h. Then, divide both sides by (4x + 2) to isolate h. This gives us h = (100 - 4x^2)/(4x + 2).

To find the maximum volume, we need to find the value of x that will give us the largest possible value for V. To do this, we can use the formula for finding the maximum value of a quadratic function, which is -b/2a. In our case, a = 4 and b = 4x + 2. So, the value of x that will give us the maximum volume is -b/2a = -(4x + 2)/(2*4) = -(4x + 2
 

1. What is optimization math?

Optimization math is a branch of mathematics that deals with finding the best possible solution to a problem. It involves using mathematical techniques to maximize or minimize a function, subject to a set of constraints.

2. Why is optimization math important?

Optimization math is important because it has a wide range of applications in various fields such as engineering, economics, operations research, and computer science. It helps in making informed decisions by finding the most efficient and effective solutions to problems.

3. What are the common techniques used in optimization math?

The most commonly used techniques in optimization math are linear programming, nonlinear programming, integer programming, and dynamic programming. These techniques use algorithms and mathematical models to find the optimal solution to a problem.

4. How do I solve optimization math problems?

To solve an optimization math problem, you first need to define the objective function and the constraints. Then, you can use various mathematical techniques and algorithms to find the optimal solution. It is important to understand the problem and choose the appropriate technique for solving it.

5. What are some real-life examples of optimization math?

Optimization math has various real-life applications, such as determining the most cost-effective production process for a manufacturing company, finding the shortest route for a delivery truck, maximizing profits for a business, and optimizing resource allocation in project management. These are just a few examples of how optimization math can be applied in real-world situations.

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