Calculating Stationary Points of a Function

In summary, Hart attempted to solve a function which has two stationary points, and found that the points are minima.
  • #1
Hart
169
0

Homework Statement



Finding the stationary point(s) of the function:

[tex]f(x,y) = xy - \frac{y^{3}}{3}[/tex]

.. on the line defined by [itex]x+y = -1[/itex].

For each point, state whether it is a minimum or maximum.

Homework Equations



.. within the problem statement and solutions.

The Attempt at a Solution



This is what I have so far:

[tex]f(x,y) = xy - \frac{y^{3}}{3}[/tex]

[tex]g(x,y) = x+y-1 = 0[/tex]

Therefore need to extemise:

[tex]F(x,y,\lambda) = f + \lambda g = xy - \frac{y^{3}}{3} + \lambda(x+y-1)[/tex]

So calculating the partial derivatives:

[tex]\frac{\partial F}{\partial x} = y + \lambda = 0[/tex]

[tex]\frac{\partial F}{\partial y} = x - 3\left(\frac{y^{2}}{3}\right) + \lambda = x - y^{2} + \lambda = 0[/tex]

[tex]\frac{\partial F}{\partial \lambda} = x + y - 1 = 0[/tex]

Then need to look for all consistent solutions:

[tex]1. y = \lambda[/tex]

.. but now I'm stuck on what to do now, seemto have done something wrong because I can't get more consistent soluations and then nice simultaneous equations to equate :confused:
 
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  • #2
Hi Hart! :smile:

(have a lambda: and a curly d: ∂ :wink:)

(Actually, it's y = -λ, isn't it? :wink:)

ok, now substitute that in the other two equations, and you'll get a quadratic equation in λ. :smile:
 
  • #3
OK.. So from the first partial derivative equation I get that:

[tex]y = -\lambda[/tex]

.. then put this into the second partial derivative equation, which gives:

[tex]x - \lambda^{2} + \lambda = 0[/tex]

.. hence:

[tex]x = \lambda^{2} - \lambda[/tex]

.. then put this into the third partial derivative equation, which gives:

[tex]\lambda^{2} - \lambda - \lambda - 1 = \lambda^{2} - 2\lambda - 1 = 0[/tex]

.. then solve quadratic equation to get values of [itex]\lambda[/itex]:

[tex]\lambda = \frac{2 \pm \sqrt{(4) + (4)}}{2} = 1 \pm \sqrt{2}[/tex]

.. hence:

[tex]\lambda = 1 + \sqrt{2} , 1 - \sqrt{2}[/tex]

.. yes??!

.. note: but:

[tex]\lambda = 1 \pm \sqrt{2} \neq - y[/tex]

:confused:
 
  • #4
What's wrong with that? :confused:

y = -1 - √2, x = 2 + √2;

y = -1 + √2, x = 2 - √2.
 
  • #5
um.. nothing! I don't know why I thought there was an issue there earlier! :redface: .. maybe just going a bit mad! :wink:

Right, so since now have:

[tex]y = -1 - \sqrt{2}, x = 2 + \sqrt{2}[/tex]

[tex]y = -1 + \sqrt{2}, x = 2 - \sqrt{2}[/tex]

.. then there are just 2 stationary points of the function, which are those 2 above?

Also, to find if the points are maxima or minima, just need to put each set of [itex](x,y)[/itex] values into this equation:

[tex]f(x,y) = xy - \frac{y^{3}}{3}[/tex]

.. and if [itex]f(x,y) > 0[/itex] then maxima point, and if [itex]f(x,y) < 0[/itex] then minima point?
 
Last edited:
  • #6
Hart said:
.. and if [itex]f(x,y) > 0[/itex] then maxima point, and if [itex]f(x,y) < 0[/itex] then minima point?

(why do you keep going into LaTeX?!)

No, that only tells you the value of f(x,y) …

you'll need more than that to check whether the value is a local maximum or minimum or stationary point.
 
  • #7
.. calculate second derivatives? negative = max point, positive = min point?
 
  • #8
Hi Hart! :smile:

(just got up :zzz: …)
Hart said:
.. calculate second derivatives? negative = max point, positive = min point?

Yes, except you'll need the second derivatives "dot" the line. :wink:
 
  • #9
erm.. so for the first set of values I have:

[tex]f(x,y) = xy - \left(\frac{y^{3}}{3}\right) = \left(\left(2+\sqrt{2}\right)\left(-1-\sqrt{2}\right)\right) - \left(\frac{\left(-1 - \sqrt{2}\right)}{3}\right) = \left(-4 - 3\sqrt{2}\right) - \left(-7 + 5\sqrt{2}\right) = 3 + 2\sqrt{2} [/tex]

which is positive, so this is a minium stationary point.

.. correct?!
 
  • #10
what happened to the second derivatives? :confused:
 
  • #11
OH.. I just forgot them! :redface:

ok, so:

[tex]f(x,y) = xy - \left(\frac{y^{3}}{3}\right)[/tex]

[tex]\frac{\partial f(x,y)}{\partial xy} = 1 - y^{2}[/tex]

[tex]\frac{\partial f(x,y)}{\partial xy} = 2y[/tex]

.. correct? (I'm not too good on partial derivations :frown:)

So then:

[tex]2y = 2\left(-1 - \sqrt{2}\right) = -2 - 2\sqrt{2}[/tex]

.. which is positive.

[tex]2y = 2\left(-1 + \sqrt{2}\right) = -2 + 2\sqrt{2}[/tex]

.. which is negative.

Hopefully somewhat getting there! :smile:
 
  • #12
hmm … this has become needlessly complicated.

It would have been easier at the beginning, instead of using the λ method (i know it has a name, but I've forgotten it :redface:), to simply use the directional derivative.

Since g(x,y) in this case is a straight line, in the direction (1,-1), all you needed to do was to find the directional derivative, ∇gf, in that direction, ie ∂f/dx - ∂f/∂y, which was y + y2 - x, and put that = 0 (subject to x + y = 1).

Substituting x = 1 - y gives ∇gf = 2y + y2 - 1 = 0 …

this is the same final equation as before, but without using λ ! :wink:

Now, to distinguish between maxima and minima, you need to know whether ∇gf is increasing or decreasing, so just consider d/dy (∇gf). :smile:
 
  • #13
.. I was doing in the [itex]\lambda[/itex] way (um.. lagrange multiplier?!) as this is how I was taught a similar problem and hence should really use this way.

Looking back through my notes on this, once the values of x and y have been found (as they have been) then just put these into the original equation for f and then can deduce if the stationary point is a min or a max.

Basically, for the first point:

[tex]x = 2 + \sqrt{2}, y = -1 - \sqrt{2}[/tex]

.. input the values into:

[tex]f(x,y) = xy - \frac{y^{3}}{3}[/tex]

and consider whether is positive or negative, and hence max or min point.

Then repeat for second point.
 
  • #14
(oh yes, Lagrange multiplier! :rolleyes:)

But the problem with that method is that f(x,y) isn't necessarily positive at a maximum or negative at a minimum.

You can change it slightly, and say that if there are only two turning-points, at A and B, then either f(A) > f(B) or f(B) > f(A) …

in either case, the first one must be a maximum, and the second a minimum! :smile:

(of course, that doesn't rule out points of inflexion, so perhaps for completeness the values towards infinity in both directions should also be considered)
 

1. How do you find the stationary points of a function?

To find the stationary points of a function, you must first take the derivative of the function and set it equal to zero. Then, solve for the variable to find the x-values of the stationary points.

2. What is the significance of stationary points in a function?

Stationary points are significant because they represent where the slope of the function is equal to zero, indicating a potential maximum or minimum point.

3. How can you determine if a stationary point is a maximum or minimum?

You can determine if a stationary point is a maximum or minimum by evaluating the second derivative of the function at the x-value of the stationary point. If the second derivative is positive, the stationary point is a minimum. If the second derivative is negative, the stationary point is a maximum.

4. Can a function have multiple stationary points?

Yes, a function can have multiple stationary points. These points can be used to identify different sections of the function, such as increasing and decreasing intervals.

5. How do you handle a function with more than one variable when calculating stationary points?

When dealing with a function with more than one variable, you must take the partial derivative with respect to each variable and set them equal to zero. Then, solve for the variables to find the critical points, which may or may not be stationary points.

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