Maximizing Cone Volume Inside a Sphere

In summary, an optimization problem is a mathematical problem that involves finding the best possible solution while satisfying given constraints. Some common types include linear programming, constrained optimization, and unconstrained optimization. These problems can be solved using methods such as gradient descent, linear programming, and branch and bound algorithms, and have real-world applications in fields such as business and engineering. However, challenges in solving optimization problems include determining the appropriate objective function, selecting the most efficient method, and dealing with complex and difficult problems.
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Homework Statement


Find the dimensions of the right circular cone of maximum volume that can be inscribed in a sphere of radius 15cm.

Homework Equations


The Attempt at a Solution



let r be radius of circular base of cone
let y be height of small right triangle
let h be height of cone
r^2 + y^2=225
y=sqrt(225-r^2)

h=15+y

V=(1/3)pir^2(sqrt(225-r^2) + 15)

Now to find V'...I get to 9r^4-2670r^2+195750 = 0
0=3(3r^4-890r^2+65250)

Need to solve for r.

Took about 2323 lines.

Final dimensions; r=11.5 roughly

h=24.63

maax volume is 3411.05 ?
 
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Can somebody confirm this? Thank you :)
 

What is an optimization problem?

An optimization problem is a type of mathematical problem that involves finding the best possible solution for a given set of constraints. The goal is to maximize or minimize an objective function, while satisfying all of the given constraints.

What are some common types of optimization problems?

Some common types of optimization problems include linear programming, constrained optimization, and unconstrained optimization. In linear programming, the objective function and constraints are all linear equations. Constrained optimization involves optimizing a function subject to one or more constraints. Unconstrained optimization involves optimizing a function without any constraints.

How do you solve optimization problems?

There are several methods for solving optimization problems, including gradient descent, linear programming, and branch and bound algorithms. The method used will depend on the specific problem and its constraints. Generally, optimization problems can be solved by either analytical or numerical methods.

What is the importance of solving optimization problems?

Optimization problems are important because they can help us find the best possible solutions to real-world problems. For example, they can be used in business to optimize production processes or in engineering to design efficient systems. Solving optimization problems can also lead to cost savings and increased efficiency.

What are some challenges in solving optimization problems?

There are several challenges in solving optimization problems, including determining the appropriate objective function, selecting the most efficient method for solving the problem, and ensuring that all constraints are met. Additionally, some optimization problems can be complex and difficult to solve, requiring advanced mathematical techniques.

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