Maximizing Area of a Racetrack: What are the Dimensions for Optimal Performance?

In summary, the problem is to find the dimensions of a racetrack that encloses the maximum area, given that it has two straight sides and semicircles at the ends. The length of the straight section can be written in terms of the radius of the end circles using the fact that the total perimeter is 400km. The area to be maximized is \pi/2 w^2, where w is the width of the rectangle. The circumference of the track is 400m, so the equation to solve is 2l + \pi/4 w^2 = 400.
  • #1
falcarius
1
0

Homework Statement


The Question is:
"A 400km racetrack is to be built with two straight sides and semicricles at the ends. Find the dimensions of the track that encloses the maximum area."

The two long sides of the rectangle are written with >/= to 100m (each)
The straight side of the 2 semi circles is written with >/= to 20m (each)
(>/= means greater than or equal to, just in case)

Homework Equations



Area of semicircle = 1/2 * pr2
Area of rectangle = lw

The Attempt at a Solution


Well i tried but its always the beginning setting up of optimization problems that is the killer, the rest is always easy. It is a study Q for an upcoming test.
 
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  • #2
Find a way to write the length of the straight section in terms of the radius of the end circles. To do this, you need to use the fact that the total perimeter is 400km.
 
  • #3
In the semicircle ends, r= w/2 where w is the "width" of the rectangle. Since there are two ends, you really have one circle. The area you want to maximize is [itex]\pi r^2= \pi/2 w^2[/itex]. As danago said, the circumference of the figure is 400 m so [itex]2l+ \pi/4 w^2= 400[/itex].
 

FAQ: Maximizing Area of a Racetrack: What are the Dimensions for Optimal Performance?

What is an optimization problem?

An optimization problem is a type of mathematical problem that involves finding the best possible solution from a set of possible solutions, often with constraints and objectives. It is commonly used in various fields such as engineering, economics, and computer science.

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There are various types of optimization problems, including linear programming, nonlinear programming, integer programming, and dynamic programming. Each type has its own characteristics and mathematical techniques for solving them.

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Solving an optimization problem involves identifying the objective function, constraints, and variables, and then using mathematical techniques such as calculus, linear algebra, and optimization algorithms to find the optimal solution.

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