Optimization Problem: Deriving the Distance Formula from a Given Diagram

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In summary, the person is seeking help with a math problem and has attached a picture of the problem and their attempt. They have found an easier method to solve the problem, but wanted a more challenging derivation by setting a different distance equal to x. However, they keep getting the wrong answer and are seeking help to understand their mistake.
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JustinLiang
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Homework Statement


I have attached a picture with the problem and my attempt. The answer is D=L/sqrt(3). I know that a much easier method to solving this is by setting the distance from B to D equal to x. However I wanted a more challenging derivation and set the distance from D to C equal to x. When I do this I keep getting the wrong answer. I have repeated the same problem three times and I am not sure why I cannot get the right answer.

Could someone please take a look at my work and give me a hint to what I have been doing wrong?

Thanks!
 

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  • #2
Homework Equations I have attached a picture with the problem and my attempt. The answer is D=L/sqrt(3). The Attempt at a Solution I have attached a picture with the problem and my attempt. The answer is D=L/sqrt(3).
 

1. What is an optimization problem?

An optimization problem is a mathematical or computational problem in which the objective is to find the best solution from a set of possible solutions. The best solution is usually the one that maximizes or minimizes a specific function or set of criteria.

2. What are some examples of optimization problems?

Common examples of optimization problems include maximizing profit, minimizing cost, finding the shortest route between two points, and maximizing the efficiency of a process or system.

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

Local optimization refers to finding the optimal solution within a specific region or range, while global optimization aims to find the best solution across all possible solutions. Local optimization methods are often faster and simpler, but may not always result in the best overall solution.

4. What are the common techniques used to solve optimization problems?

Some common techniques used to solve optimization problems include linear programming, gradient descent, genetic algorithms, and simulated annealing. The choice of technique depends on the specific problem and its constraints.

5. How are optimization problems used in real-world applications?

Optimization problems are used in a wide range of fields, including engineering, economics, finance, logistics, and computer science. They can be used to improve efficiency, reduce costs, and make better decisions in various industries and processes.

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