Finding Max & Min of Optimization Problem: How To Distinguish

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In summary, the process for finding the max and min of an optimization problem involves finding the critical values and using the first or second derivative tests. The first derivative test involves finding the critical numbers and using them to determine the nature of the extremum. The second derivative test involves using the second derivative to find the critical numbers and then determining whether they are minima or maxima based on the sign of the derivative. Both tests are used to find the extremum and are based on the concept of the derivative representing the rate of change and the slope of the function.
  • #1
thinkbot
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How are Finding the max and min of a optimization problem different. and how do you distinguish them in an equation?
 
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  • #2
Finding the critical values is the same, and then we can use either the first or second derivative tests to determine the nature of the extremum, or whether it is actually an extremum or not.

Are you familiar with these two tests?
 
  • #3
Yes I am familiar
 
  • #4
thinkbot said:
Yes I am familiar

Can you briefly explain how they work? :D
 
  • #5
find f^1(x) = 0 x('s)= critical numbers plus some points (a,b) or [a,b]
f(x,a,b) = extrema Larget # max smallest # min
Using f^2(x) for the critical #'s f2(x) > 0 then min and ect.
 
  • #6
thinkbot said:
find f^1(x) = 0 x('s)= critical numbers plus some points (a,b) or [a,b]
f(x,a,b) = extrema Larget # max smallest # min
Using f^2(x) for the critical #'s f2(x) > 0 then min and ect.

I meant can you explain how and why the first and second derivative tests for relative extrema work, i.e., the rationale behind them.
 

FAQ: Finding Max & Min of Optimization Problem: How To Distinguish

How do you define optimization problems?

Optimization problems are mathematical problems that involve finding the maximum or minimum value of a function, while satisfying a set of constraints. They are used to model real-world scenarios and find the best possible solution to a given problem.

What is the difference between local and global maxima/minima?

Local maxima/minima refer to the highest or lowest point in a small neighborhood of a function, while global maxima/minima are the highest or lowest point in the entire domain of the function. In optimization problems, we are interested in finding the global maxima/minima.

How do you distinguish between critical points and endpoints?

Critical points are points where the derivative of a function is equal to zero, while endpoints are points at the boundaries of the function's domain. To find the maxima/minima of a function, we need to consider both critical points and endpoints.

What is the role of the second derivative in finding maxima/minima?

The second derivative of a function at a critical point helps us determine whether that point is a local maxima, local minima, or a point of inflection. This information is crucial in finding the global maxima/minima of an optimization problem.

How can we use calculus to solve optimization problems?

Calculus provides us with the tools to find the critical points of a function and determine whether they are maxima or minima. By setting up and solving equations based on the given constraints, we can find the optimal solution to an optimization problem.

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