Stationary points in local optimization

In summary, the conversation discusses finding the stationary points of a given function and comparing the derivatives to 0. The user initially finds 3 points, but upon further examination, realizes that there should be 4 points and is able to find the missing point by solving a system of equations.
  • #1
Yankel
395
0
Hello again,

I have a small problem. I am looking for local minimum and maximum points of the function:

\[f(x,y)=3x^{2}y+y^{3}-3x^{2}-3y^{2}+2\]

The first question was how many stationary points are there. I have found the derivatives by x and y:

\[f_{x}=6xy-6x\]

\[f_{y}=3x^{2}+3y^{2}-6y\]

and compared them to 0. I found 3 points: y=0,1,2.

According to the attached answers, there should be 4. There is either a mistake in the answer attached, or I am missing a point. Can you help me solve the system of two equations please to find all the points ? Thank you !

- - - Updated - - -

Ok, I couldn't find a DELETE button, so I will answer my own question.

When I put the 3 (!) values of y back in the equations, for one of them, x got 2 values, bringing the sum of points to 4. My mistake.
 
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  • #2
We don't allow users to delete threads (which is what would happen to a thread if the first post in it is deleted) because that could potentially cause valuable content to be destroyed if a user decided to delete their thread after getting help because they are trying to keep their professor from finding the thread. :D

Your partials look correct, and from them we obtain:

\(\displaystyle x(y-1)=0\)

\(\displaystyle x^2+(y-1)^2=1\)

And as you found, when from the first equation we take $x=0$, we find \(\displaystyle y=1\pm1\), and for \(\displaystyle y=1\) we find \(\displaystyle x=\pm1\) for a total of 4 points. :D
 

FAQ: Stationary points in local optimization

What are stationary points in local optimization?

Stationary points in local optimization refer to points on a graph where the derivative of a function is equal to zero. These points can be either maximum or minimum points of the function.

How do stationary points affect local optimization?

Stationary points play a crucial role in local optimization as they indicate the potential location of optimal solutions. By identifying and analyzing these points, we can determine the direction and magnitude of change in the function, ultimately leading to the optimal solution.

How do I identify stationary points?

To identify stationary points, we take the first derivative of the function and set it equal to zero. We then solve for the variable to find the x-value(s) of the stationary point(s). We can also use the second derivative test to determine if the stationary point is a maximum or minimum.

Can there be multiple stationary points in a function?

Yes, there can be multiple stationary points in a function. This usually occurs when the function has multiple turns or inflection points. It is important to analyze each stationary point to determine which one is the optimal solution.

How do stationary points differ from global optima?

While stationary points refer to points where the derivative is equal to zero, global optima are the absolute maximum or minimum points of a function. A stationary point may not necessarily be a global optimum, as there could be other points on the function that have a higher or lower value. However, stationary points can help us identify potential global optima in local optimization.

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