Is this optimization problem missing information?

In summary, the conversation involves a question about finding the minimum weight of a tank with a square base and open top, made of a sheet of steel with a given thickness. The weight is determined by a constant times the surface area of the tank. The conversation ends with the questioner successfully solving the problem with some guidance.
  • #1
mharten1
62
0

Homework Statement



A 5324 cubic foot tank with square base and an open top is to be constructed of a sheet of steel of a given thickness. Find the length of a side of the square base of the tank with minimum weight.

Homework Equations


The Attempt at a Solution



I'm usually fairly decent at optimization questions. Is this solvable with the given information? It seems to me to be missing something because no values or relationships are ever assigned to weight. I don't even know where to start; I can easily set up an equation for volume, but I also need to find an equation for weight. If you think it's solvable, please do not give me the solution. Just nudge me in the correct direction. :)
 
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  • #2
The weight of the tank is some constant times the surface area of the tank.
When you try to solve it, you'll find this constant is irrelevant. :)
 
  • #3
Thanks, I was able to solve it perfectly. :P
 
  • #4
You're welcome! :smile:
 

Related to Is this optimization problem missing information?

1. What is an optimization problem?

An optimization problem is a mathematical problem that involves finding the best solution or outcome from a set of possible options. This can involve maximizing or minimizing a certain value, subject to certain constraints or limitations.

2. How do you know if an optimization problem is missing information?

An optimization problem is considered to be missing information if there are unknown variables or parameters that are not clearly defined or provided in the problem statement. This can make it difficult or impossible to find a solution using standard optimization methods.

3. What are some common types of missing information in optimization problems?

Some common types of missing information in optimization problems include missing constraints, missing objective functions, and missing values for certain variables or parameters. Other types of missing information can include incorrect or incomplete data, or unclear problem specifications.

4. How can missing information affect the solution to an optimization problem?

If an optimization problem is missing critical information, it can make it impossible to find a solution using traditional optimization methods. This can lead to incorrect or suboptimal solutions, or even make the problem unsolvable. In some cases, it may be necessary to make assumptions or estimations about the missing information in order to find a feasible solution.

5. What steps can be taken to address missing information in an optimization problem?

If an optimization problem is missing information, it is important to carefully analyze the problem and identify the missing elements. This can involve making assumptions or estimations about the missing information, or seeking clarification from the problem owner or stakeholders. In some cases, it may be necessary to reformulate the problem or use alternative optimization methods to find a viable solution.

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