Find the maximum and minimum (there are four in total) that the function $f(x,y)=3xy$ achieves when $(x,y)$...












1












$begingroup$


Find the maximum and minimum (there are four in total) that the function $f(x,y)=3xy$ achieves when $(x,y)$ travel the ellipse $x^2+y^2+xy=3$



I have thought about doing the following but I do not know if I am doing the right thing:



I'm using Lagrange multipliers and I start with $bigtriangledown f=lambdabigtriangledown g$, so from this I get $(3y,3x)=lambda(2x+y,2y+x)$ so $lambda=frac{3y}{2x+y}$ and $lambda=frac{3x}{2y+x}$ so $frac{3y}{2x+y}=frac{3x}{2y+x}$ so $x^2=y^2$ so $y=pm x$. So, I get to that $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and $(-sqrt{3},sqrt{3})$ are critical points, the problem is that I do not know how to determine if they are maximum or minimum, how can I do this? Thank you.










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  • 2




    $begingroup$
    Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
    $endgroup$
    – Martin R
    Jan 4 at 4:10












  • $begingroup$
    @MartinR Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55
















1












$begingroup$


Find the maximum and minimum (there are four in total) that the function $f(x,y)=3xy$ achieves when $(x,y)$ travel the ellipse $x^2+y^2+xy=3$



I have thought about doing the following but I do not know if I am doing the right thing:



I'm using Lagrange multipliers and I start with $bigtriangledown f=lambdabigtriangledown g$, so from this I get $(3y,3x)=lambda(2x+y,2y+x)$ so $lambda=frac{3y}{2x+y}$ and $lambda=frac{3x}{2y+x}$ so $frac{3y}{2x+y}=frac{3x}{2y+x}$ so $x^2=y^2$ so $y=pm x$. So, I get to that $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and $(-sqrt{3},sqrt{3})$ are critical points, the problem is that I do not know how to determine if they are maximum or minimum, how can I do this? Thank you.










share|cite|improve this question











$endgroup$








  • 2




    $begingroup$
    Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
    $endgroup$
    – Martin R
    Jan 4 at 4:10












  • $begingroup$
    @MartinR Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55














1












1








1


2



$begingroup$


Find the maximum and minimum (there are four in total) that the function $f(x,y)=3xy$ achieves when $(x,y)$ travel the ellipse $x^2+y^2+xy=3$



I have thought about doing the following but I do not know if I am doing the right thing:



I'm using Lagrange multipliers and I start with $bigtriangledown f=lambdabigtriangledown g$, so from this I get $(3y,3x)=lambda(2x+y,2y+x)$ so $lambda=frac{3y}{2x+y}$ and $lambda=frac{3x}{2y+x}$ so $frac{3y}{2x+y}=frac{3x}{2y+x}$ so $x^2=y^2$ so $y=pm x$. So, I get to that $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and $(-sqrt{3},sqrt{3})$ are critical points, the problem is that I do not know how to determine if they are maximum or minimum, how can I do this? Thank you.










share|cite|improve this question











$endgroup$




Find the maximum and minimum (there are four in total) that the function $f(x,y)=3xy$ achieves when $(x,y)$ travel the ellipse $x^2+y^2+xy=3$



I have thought about doing the following but I do not know if I am doing the right thing:



I'm using Lagrange multipliers and I start with $bigtriangledown f=lambdabigtriangledown g$, so from this I get $(3y,3x)=lambda(2x+y,2y+x)$ so $lambda=frac{3y}{2x+y}$ and $lambda=frac{3x}{2y+x}$ so $frac{3y}{2x+y}=frac{3x}{2y+x}$ so $x^2=y^2$ so $y=pm x$. So, I get to that $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and $(-sqrt{3},sqrt{3})$ are critical points, the problem is that I do not know how to determine if they are maximum or minimum, how can I do this? Thank you.







real-analysis multivariable-calculus optimization lagrange-multiplier maxima-minima






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share|cite|improve this question













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edited Jan 4 at 7:20









Michael Rozenberg

108k1895200




108k1895200










asked Jan 4 at 3:47









NashNash

58549




58549








  • 2




    $begingroup$
    Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
    $endgroup$
    – Martin R
    Jan 4 at 4:10












  • $begingroup$
    @MartinR Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55














  • 2




    $begingroup$
    Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
    $endgroup$
    – Martin R
    Jan 4 at 4:10












  • $begingroup$
    @MartinR Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55








2




2




$begingroup$
Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
$endgroup$
– Martin R
Jan 4 at 4:10






$begingroup$
Just compute f at those 4 points. Btw, (0,0) is not on the ellipse.
$endgroup$
– Martin R
Jan 4 at 4:10














$begingroup$
@MartinR Is what I did fine?
$endgroup$
– Nash
Jan 4 at 20:55




$begingroup$
@MartinR Is what I did fine?
$endgroup$
– Nash
Jan 4 at 20:55










7 Answers
7






active

oldest

votes


















3












$begingroup$

If $x,y$ have the same sign $f(x,y)>0$



and if they have opposite signs $f(x,y)<0$



With the 4 pairs you have, 2 share the same sign and and 2 do not. That should make it clear wich are the maxima and which are the minima.



But is calculus even necessary?



Make this substitution



$x = u+v\
y = u-v$



Then your objective and constraint become:



$f(u,v) = 3u^2 - 3v^2\
3u^2 + v^2 = 3$



Plugging the constraint into the objective.



$f(u,v) = 3 - 4v^2$



$f$ is maximized when $v = 0$



$u = pm 1\
x = pm 1\
y = pm 1$



$f$ is minimized when $u = 0$



$v = pm sqrt 3\
x = pm sqrt 3\
y = mp sqrt 3$






share|cite|improve this answer











$endgroup$













  • $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55






  • 1




    $begingroup$
    Your work on with the Lagrange multipliers was fine.
    $endgroup$
    – Doug M
    Jan 4 at 21:10



















2












$begingroup$

Let $3xy=k$.



Thus,
$$k(x^2+y^2+xy)=9xy$$ or
$$kx^2+(k-9)xy+ky^2=0$$ has solutions.



Let $kneq0$.



Thus, $$(k-9)^2-4k^2geq0$$ or
$$(k+9)(k-3)leq0$$ or
$$-9leq kleq3.$$
Now, we see that $k=0$ is not relevant and the extreme value of $k$ occurs for $x=-frac{k-9}{2k}y$,



which says that
$$max_{x^2+y^2+xy=3}3xy=3$$ and
$$min_{x^2+y^2+xy=3}3xy=-9$$






share|cite|improve this answer









$endgroup$













  • $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56






  • 1




    $begingroup$
    @Nash Without the point $(0,0)$ it looks fine.
    $endgroup$
    – Michael Rozenberg
    Jan 4 at 20:58



















2












$begingroup$

If Lagrange multipliers is not mandatory,



$$12=4x^2+4y^2+4xy=(2x+y)^2+(sqrt3y)^2$$



Let $sqrt3y=sqrt{12}cos tiff y=2cos t$



$2x+y=2sqrt3sin tiff 2x=2sqrt3sin t-2cos tiff x=sqrt3sin t-cos t=2sinleft(t-30^circright)$



$3xy=12cos tsinleft(t-30^circright)=6[sin(2t-30^circ)-sin30^circ]$



Now for real $x,y;t$ is real $$-1lesin(2t-30^circ)le1$$






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  • $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56



















1












$begingroup$

Evaluate your function $f(x,y) = 3xy$ at each of these four points, $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and compare the results.You will find maximum is achieved at $(1,1)$ and $(-1,-1)$ and minimum is achieved at $ pm (sqrt 3, -sqrt 3)$






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$endgroup$













  • $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56










  • $begingroup$
    Yes your work is correct
    $endgroup$
    – Mohammad Riazi-Kermani
    Jan 4 at 22:55



















1












$begingroup$

As the equations involved are homogeneous, making $y = lambda x$ we have



$$
min(max)3x^2lambda mbox{s. t. } x^2(1+lambda^2+lambda) = 3
$$



which is equivalent to



$$
min_{lambda}(max_{lambda})f(lambda) = frac{9lambda}{lambda^2+lambda+1}
$$



so the stationary points are at



$$
f'(lambda) = -frac{9 left(lambda ^2-1right)}{left(lambda ^2+lambda +1right)^2} = 0Rightarrow lambda^* = {-1,1}
$$



then the solutions are at $y = pm x$ etc.






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$endgroup$













  • $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56



















1












$begingroup$

1) $(x+y)^2- xy= 3;$



$xy = (x+y)^2 -3;$



$f(x,y)=3xy = 3(x+y)^2-9.$



$f_{min}=-9$, at $x=-y$;



$-3x^2= -9; x=pm √3; y=mp √3$;



2) $(x-y)^2+3xy= 3;$



$f(x,y)= 3xy= 3-(x-y)^2$;



$f_{max}= 3$, at $x=y$.



$x^2=1$; $x =pm 1$, $y=pm 1$.






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$endgroup$





















    0












    $begingroup$

    You can determine the "type" of the critical point using the partial derivatives. Suppose $(x,y)$ is a critical point that you are considering. Then,




    1. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} > 0$ when evaluated at $(x,y)$, then there is a relative minimum at $(x,y)$.

    2. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} < 0$, you have a relative minimum.

    3. If $f_{xx} f_{yy}- (f_{xx})^2 < 0$ then you've got a saddle point.

    4. If $f_{xx} f_{yy}- (f_{xx})^2 = 0$ its indeterminate.


    Edit: Just looked at the function you've provided. Clearly, it's going to indeterminate since the second derivative for $x$ or $y$ is $0$. You'll have to just plug in the values of the critical points you've found and determine it based on that.






    share|cite|improve this answer









    $endgroup$









    • 1




      $begingroup$
      This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
      $endgroup$
      – Will M.
      Jan 4 at 4:36






    • 1




      $begingroup$
      Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
      $endgroup$
      – amd
      Jan 4 at 4:47











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    7 Answers
    7






    active

    oldest

    votes








    7 Answers
    7






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    3












    $begingroup$

    If $x,y$ have the same sign $f(x,y)>0$



    and if they have opposite signs $f(x,y)<0$



    With the 4 pairs you have, 2 share the same sign and and 2 do not. That should make it clear wich are the maxima and which are the minima.



    But is calculus even necessary?



    Make this substitution



    $x = u+v\
    y = u-v$



    Then your objective and constraint become:



    $f(u,v) = 3u^2 - 3v^2\
    3u^2 + v^2 = 3$



    Plugging the constraint into the objective.



    $f(u,v) = 3 - 4v^2$



    $f$ is maximized when $v = 0$



    $u = pm 1\
    x = pm 1\
    y = pm 1$



    $f$ is minimized when $u = 0$



    $v = pm sqrt 3\
    x = pm sqrt 3\
    y = mp sqrt 3$






    share|cite|improve this answer











    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:55






    • 1




      $begingroup$
      Your work on with the Lagrange multipliers was fine.
      $endgroup$
      – Doug M
      Jan 4 at 21:10
















    3












    $begingroup$

    If $x,y$ have the same sign $f(x,y)>0$



    and if they have opposite signs $f(x,y)<0$



    With the 4 pairs you have, 2 share the same sign and and 2 do not. That should make it clear wich are the maxima and which are the minima.



    But is calculus even necessary?



    Make this substitution



    $x = u+v\
    y = u-v$



    Then your objective and constraint become:



    $f(u,v) = 3u^2 - 3v^2\
    3u^2 + v^2 = 3$



    Plugging the constraint into the objective.



    $f(u,v) = 3 - 4v^2$



    $f$ is maximized when $v = 0$



    $u = pm 1\
    x = pm 1\
    y = pm 1$



    $f$ is minimized when $u = 0$



    $v = pm sqrt 3\
    x = pm sqrt 3\
    y = mp sqrt 3$






    share|cite|improve this answer











    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:55






    • 1




      $begingroup$
      Your work on with the Lagrange multipliers was fine.
      $endgroup$
      – Doug M
      Jan 4 at 21:10














    3












    3








    3





    $begingroup$

    If $x,y$ have the same sign $f(x,y)>0$



    and if they have opposite signs $f(x,y)<0$



    With the 4 pairs you have, 2 share the same sign and and 2 do not. That should make it clear wich are the maxima and which are the minima.



    But is calculus even necessary?



    Make this substitution



    $x = u+v\
    y = u-v$



    Then your objective and constraint become:



    $f(u,v) = 3u^2 - 3v^2\
    3u^2 + v^2 = 3$



    Plugging the constraint into the objective.



    $f(u,v) = 3 - 4v^2$



    $f$ is maximized when $v = 0$



    $u = pm 1\
    x = pm 1\
    y = pm 1$



    $f$ is minimized when $u = 0$



    $v = pm sqrt 3\
    x = pm sqrt 3\
    y = mp sqrt 3$






    share|cite|improve this answer











    $endgroup$



    If $x,y$ have the same sign $f(x,y)>0$



    and if they have opposite signs $f(x,y)<0$



    With the 4 pairs you have, 2 share the same sign and and 2 do not. That should make it clear wich are the maxima and which are the minima.



    But is calculus even necessary?



    Make this substitution



    $x = u+v\
    y = u-v$



    Then your objective and constraint become:



    $f(u,v) = 3u^2 - 3v^2\
    3u^2 + v^2 = 3$



    Plugging the constraint into the objective.



    $f(u,v) = 3 - 4v^2$



    $f$ is maximized when $v = 0$



    $u = pm 1\
    x = pm 1\
    y = pm 1$



    $f$ is minimized when $u = 0$



    $v = pm sqrt 3\
    x = pm sqrt 3\
    y = mp sqrt 3$







    share|cite|improve this answer














    share|cite|improve this answer



    share|cite|improve this answer








    edited Jan 4 at 7:24

























    answered Jan 4 at 4:25









    Doug MDoug M

    45.3k31954




    45.3k31954












    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:55






    • 1




      $begingroup$
      Your work on with the Lagrange multipliers was fine.
      $endgroup$
      – Doug M
      Jan 4 at 21:10


















    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:55






    • 1




      $begingroup$
      Your work on with the Lagrange multipliers was fine.
      $endgroup$
      – Doug M
      Jan 4 at 21:10
















    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55




    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:55




    1




    1




    $begingroup$
    Your work on with the Lagrange multipliers was fine.
    $endgroup$
    – Doug M
    Jan 4 at 21:10




    $begingroup$
    Your work on with the Lagrange multipliers was fine.
    $endgroup$
    – Doug M
    Jan 4 at 21:10











    2












    $begingroup$

    Let $3xy=k$.



    Thus,
    $$k(x^2+y^2+xy)=9xy$$ or
    $$kx^2+(k-9)xy+ky^2=0$$ has solutions.



    Let $kneq0$.



    Thus, $$(k-9)^2-4k^2geq0$$ or
    $$(k+9)(k-3)leq0$$ or
    $$-9leq kleq3.$$
    Now, we see that $k=0$ is not relevant and the extreme value of $k$ occurs for $x=-frac{k-9}{2k}y$,



    which says that
    $$max_{x^2+y^2+xy=3}3xy=3$$ and
    $$min_{x^2+y^2+xy=3}3xy=-9$$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56






    • 1




      $begingroup$
      @Nash Without the point $(0,0)$ it looks fine.
      $endgroup$
      – Michael Rozenberg
      Jan 4 at 20:58
















    2












    $begingroup$

    Let $3xy=k$.



    Thus,
    $$k(x^2+y^2+xy)=9xy$$ or
    $$kx^2+(k-9)xy+ky^2=0$$ has solutions.



    Let $kneq0$.



    Thus, $$(k-9)^2-4k^2geq0$$ or
    $$(k+9)(k-3)leq0$$ or
    $$-9leq kleq3.$$
    Now, we see that $k=0$ is not relevant and the extreme value of $k$ occurs for $x=-frac{k-9}{2k}y$,



    which says that
    $$max_{x^2+y^2+xy=3}3xy=3$$ and
    $$min_{x^2+y^2+xy=3}3xy=-9$$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56






    • 1




      $begingroup$
      @Nash Without the point $(0,0)$ it looks fine.
      $endgroup$
      – Michael Rozenberg
      Jan 4 at 20:58














    2












    2








    2





    $begingroup$

    Let $3xy=k$.



    Thus,
    $$k(x^2+y^2+xy)=9xy$$ or
    $$kx^2+(k-9)xy+ky^2=0$$ has solutions.



    Let $kneq0$.



    Thus, $$(k-9)^2-4k^2geq0$$ or
    $$(k+9)(k-3)leq0$$ or
    $$-9leq kleq3.$$
    Now, we see that $k=0$ is not relevant and the extreme value of $k$ occurs for $x=-frac{k-9}{2k}y$,



    which says that
    $$max_{x^2+y^2+xy=3}3xy=3$$ and
    $$min_{x^2+y^2+xy=3}3xy=-9$$






    share|cite|improve this answer









    $endgroup$



    Let $3xy=k$.



    Thus,
    $$k(x^2+y^2+xy)=9xy$$ or
    $$kx^2+(k-9)xy+ky^2=0$$ has solutions.



    Let $kneq0$.



    Thus, $$(k-9)^2-4k^2geq0$$ or
    $$(k+9)(k-3)leq0$$ or
    $$-9leq kleq3.$$
    Now, we see that $k=0$ is not relevant and the extreme value of $k$ occurs for $x=-frac{k-9}{2k}y$,



    which says that
    $$max_{x^2+y^2+xy=3}3xy=3$$ and
    $$min_{x^2+y^2+xy=3}3xy=-9$$







    share|cite|improve this answer












    share|cite|improve this answer



    share|cite|improve this answer










    answered Jan 4 at 7:16









    Michael RozenbergMichael Rozenberg

    108k1895200




    108k1895200












    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56






    • 1




      $begingroup$
      @Nash Without the point $(0,0)$ it looks fine.
      $endgroup$
      – Michael Rozenberg
      Jan 4 at 20:58


















    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56






    • 1




      $begingroup$
      @Nash Without the point $(0,0)$ it looks fine.
      $endgroup$
      – Michael Rozenberg
      Jan 4 at 20:58
















    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56




    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56




    1




    1




    $begingroup$
    @Nash Without the point $(0,0)$ it looks fine.
    $endgroup$
    – Michael Rozenberg
    Jan 4 at 20:58




    $begingroup$
    @Nash Without the point $(0,0)$ it looks fine.
    $endgroup$
    – Michael Rozenberg
    Jan 4 at 20:58











    2












    $begingroup$

    If Lagrange multipliers is not mandatory,



    $$12=4x^2+4y^2+4xy=(2x+y)^2+(sqrt3y)^2$$



    Let $sqrt3y=sqrt{12}cos tiff y=2cos t$



    $2x+y=2sqrt3sin tiff 2x=2sqrt3sin t-2cos tiff x=sqrt3sin t-cos t=2sinleft(t-30^circright)$



    $3xy=12cos tsinleft(t-30^circright)=6[sin(2t-30^circ)-sin30^circ]$



    Now for real $x,y;t$ is real $$-1lesin(2t-30^circ)le1$$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56
















    2












    $begingroup$

    If Lagrange multipliers is not mandatory,



    $$12=4x^2+4y^2+4xy=(2x+y)^2+(sqrt3y)^2$$



    Let $sqrt3y=sqrt{12}cos tiff y=2cos t$



    $2x+y=2sqrt3sin tiff 2x=2sqrt3sin t-2cos tiff x=sqrt3sin t-cos t=2sinleft(t-30^circright)$



    $3xy=12cos tsinleft(t-30^circright)=6[sin(2t-30^circ)-sin30^circ]$



    Now for real $x,y;t$ is real $$-1lesin(2t-30^circ)le1$$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56














    2












    2








    2





    $begingroup$

    If Lagrange multipliers is not mandatory,



    $$12=4x^2+4y^2+4xy=(2x+y)^2+(sqrt3y)^2$$



    Let $sqrt3y=sqrt{12}cos tiff y=2cos t$



    $2x+y=2sqrt3sin tiff 2x=2sqrt3sin t-2cos tiff x=sqrt3sin t-cos t=2sinleft(t-30^circright)$



    $3xy=12cos tsinleft(t-30^circright)=6[sin(2t-30^circ)-sin30^circ]$



    Now for real $x,y;t$ is real $$-1lesin(2t-30^circ)le1$$






    share|cite|improve this answer









    $endgroup$



    If Lagrange multipliers is not mandatory,



    $$12=4x^2+4y^2+4xy=(2x+y)^2+(sqrt3y)^2$$



    Let $sqrt3y=sqrt{12}cos tiff y=2cos t$



    $2x+y=2sqrt3sin tiff 2x=2sqrt3sin t-2cos tiff x=sqrt3sin t-cos t=2sinleft(t-30^circright)$



    $3xy=12cos tsinleft(t-30^circright)=6[sin(2t-30^circ)-sin30^circ]$



    Now for real $x,y;t$ is real $$-1lesin(2t-30^circ)le1$$







    share|cite|improve this answer












    share|cite|improve this answer



    share|cite|improve this answer










    answered Jan 4 at 11:47









    lab bhattacharjeelab bhattacharjee

    226k15158275




    226k15158275












    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56


















    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56
















    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56




    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56











    1












    $begingroup$

    Evaluate your function $f(x,y) = 3xy$ at each of these four points, $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and compare the results.You will find maximum is achieved at $(1,1)$ and $(-1,-1)$ and minimum is achieved at $ pm (sqrt 3, -sqrt 3)$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56










    • $begingroup$
      Yes your work is correct
      $endgroup$
      – Mohammad Riazi-Kermani
      Jan 4 at 22:55
















    1












    $begingroup$

    Evaluate your function $f(x,y) = 3xy$ at each of these four points, $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and compare the results.You will find maximum is achieved at $(1,1)$ and $(-1,-1)$ and minimum is achieved at $ pm (sqrt 3, -sqrt 3)$






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56










    • $begingroup$
      Yes your work is correct
      $endgroup$
      – Mohammad Riazi-Kermani
      Jan 4 at 22:55














    1












    1








    1





    $begingroup$

    Evaluate your function $f(x,y) = 3xy$ at each of these four points, $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and compare the results.You will find maximum is achieved at $(1,1)$ and $(-1,-1)$ and minimum is achieved at $ pm (sqrt 3, -sqrt 3)$






    share|cite|improve this answer









    $endgroup$



    Evaluate your function $f(x,y) = 3xy$ at each of these four points, $(0,0), (1,1), (-1,-1), (sqrt{3},-sqrt{3})$ and compare the results.You will find maximum is achieved at $(1,1)$ and $(-1,-1)$ and minimum is achieved at $ pm (sqrt 3, -sqrt 3)$







    share|cite|improve this answer












    share|cite|improve this answer



    share|cite|improve this answer










    answered Jan 4 at 4:17









    Mohammad Riazi-KermaniMohammad Riazi-Kermani

    41.6k42061




    41.6k42061












    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56










    • $begingroup$
      Yes your work is correct
      $endgroup$
      – Mohammad Riazi-Kermani
      Jan 4 at 22:55


















    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56










    • $begingroup$
      Yes your work is correct
      $endgroup$
      – Mohammad Riazi-Kermani
      Jan 4 at 22:55
















    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56




    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56












    $begingroup$
    Yes your work is correct
    $endgroup$
    – Mohammad Riazi-Kermani
    Jan 4 at 22:55




    $begingroup$
    Yes your work is correct
    $endgroup$
    – Mohammad Riazi-Kermani
    Jan 4 at 22:55











    1












    $begingroup$

    As the equations involved are homogeneous, making $y = lambda x$ we have



    $$
    min(max)3x^2lambda mbox{s. t. } x^2(1+lambda^2+lambda) = 3
    $$



    which is equivalent to



    $$
    min_{lambda}(max_{lambda})f(lambda) = frac{9lambda}{lambda^2+lambda+1}
    $$



    so the stationary points are at



    $$
    f'(lambda) = -frac{9 left(lambda ^2-1right)}{left(lambda ^2+lambda +1right)^2} = 0Rightarrow lambda^* = {-1,1}
    $$



    then the solutions are at $y = pm x$ etc.






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56
















    1












    $begingroup$

    As the equations involved are homogeneous, making $y = lambda x$ we have



    $$
    min(max)3x^2lambda mbox{s. t. } x^2(1+lambda^2+lambda) = 3
    $$



    which is equivalent to



    $$
    min_{lambda}(max_{lambda})f(lambda) = frac{9lambda}{lambda^2+lambda+1}
    $$



    so the stationary points are at



    $$
    f'(lambda) = -frac{9 left(lambda ^2-1right)}{left(lambda ^2+lambda +1right)^2} = 0Rightarrow lambda^* = {-1,1}
    $$



    then the solutions are at $y = pm x$ etc.






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56














    1












    1








    1





    $begingroup$

    As the equations involved are homogeneous, making $y = lambda x$ we have



    $$
    min(max)3x^2lambda mbox{s. t. } x^2(1+lambda^2+lambda) = 3
    $$



    which is equivalent to



    $$
    min_{lambda}(max_{lambda})f(lambda) = frac{9lambda}{lambda^2+lambda+1}
    $$



    so the stationary points are at



    $$
    f'(lambda) = -frac{9 left(lambda ^2-1right)}{left(lambda ^2+lambda +1right)^2} = 0Rightarrow lambda^* = {-1,1}
    $$



    then the solutions are at $y = pm x$ etc.






    share|cite|improve this answer









    $endgroup$



    As the equations involved are homogeneous, making $y = lambda x$ we have



    $$
    min(max)3x^2lambda mbox{s. t. } x^2(1+lambda^2+lambda) = 3
    $$



    which is equivalent to



    $$
    min_{lambda}(max_{lambda})f(lambda) = frac{9lambda}{lambda^2+lambda+1}
    $$



    so the stationary points are at



    $$
    f'(lambda) = -frac{9 left(lambda ^2-1right)}{left(lambda ^2+lambda +1right)^2} = 0Rightarrow lambda^* = {-1,1}
    $$



    then the solutions are at $y = pm x$ etc.







    share|cite|improve this answer












    share|cite|improve this answer



    share|cite|improve this answer










    answered Jan 4 at 12:16









    CesareoCesareo

    9,3363517




    9,3363517












    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56


















    • $begingroup$
      Is what I did fine?
      $endgroup$
      – Nash
      Jan 4 at 20:56
















    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56




    $begingroup$
    Is what I did fine?
    $endgroup$
    – Nash
    Jan 4 at 20:56











    1












    $begingroup$

    1) $(x+y)^2- xy= 3;$



    $xy = (x+y)^2 -3;$



    $f(x,y)=3xy = 3(x+y)^2-9.$



    $f_{min}=-9$, at $x=-y$;



    $-3x^2= -9; x=pm √3; y=mp √3$;



    2) $(x-y)^2+3xy= 3;$



    $f(x,y)= 3xy= 3-(x-y)^2$;



    $f_{max}= 3$, at $x=y$.



    $x^2=1$; $x =pm 1$, $y=pm 1$.






    share|cite|improve this answer











    $endgroup$


















      1












      $begingroup$

      1) $(x+y)^2- xy= 3;$



      $xy = (x+y)^2 -3;$



      $f(x,y)=3xy = 3(x+y)^2-9.$



      $f_{min}=-9$, at $x=-y$;



      $-3x^2= -9; x=pm √3; y=mp √3$;



      2) $(x-y)^2+3xy= 3;$



      $f(x,y)= 3xy= 3-(x-y)^2$;



      $f_{max}= 3$, at $x=y$.



      $x^2=1$; $x =pm 1$, $y=pm 1$.






      share|cite|improve this answer











      $endgroup$
















        1












        1








        1





        $begingroup$

        1) $(x+y)^2- xy= 3;$



        $xy = (x+y)^2 -3;$



        $f(x,y)=3xy = 3(x+y)^2-9.$



        $f_{min}=-9$, at $x=-y$;



        $-3x^2= -9; x=pm √3; y=mp √3$;



        2) $(x-y)^2+3xy= 3;$



        $f(x,y)= 3xy= 3-(x-y)^2$;



        $f_{max}= 3$, at $x=y$.



        $x^2=1$; $x =pm 1$, $y=pm 1$.






        share|cite|improve this answer











        $endgroup$



        1) $(x+y)^2- xy= 3;$



        $xy = (x+y)^2 -3;$



        $f(x,y)=3xy = 3(x+y)^2-9.$



        $f_{min}=-9$, at $x=-y$;



        $-3x^2= -9; x=pm √3; y=mp √3$;



        2) $(x-y)^2+3xy= 3;$



        $f(x,y)= 3xy= 3-(x-y)^2$;



        $f_{max}= 3$, at $x=y$.



        $x^2=1$; $x =pm 1$, $y=pm 1$.







        share|cite|improve this answer














        share|cite|improve this answer



        share|cite|improve this answer








        edited Jan 4 at 21:12

























        answered Jan 4 at 7:22









        Peter SzilasPeter Szilas

        11.5k2822




        11.5k2822























            0












            $begingroup$

            You can determine the "type" of the critical point using the partial derivatives. Suppose $(x,y)$ is a critical point that you are considering. Then,




            1. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} > 0$ when evaluated at $(x,y)$, then there is a relative minimum at $(x,y)$.

            2. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} < 0$, you have a relative minimum.

            3. If $f_{xx} f_{yy}- (f_{xx})^2 < 0$ then you've got a saddle point.

            4. If $f_{xx} f_{yy}- (f_{xx})^2 = 0$ its indeterminate.


            Edit: Just looked at the function you've provided. Clearly, it's going to indeterminate since the second derivative for $x$ or $y$ is $0$. You'll have to just plug in the values of the critical points you've found and determine it based on that.






            share|cite|improve this answer









            $endgroup$









            • 1




              $begingroup$
              This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
              $endgroup$
              – Will M.
              Jan 4 at 4:36






            • 1




              $begingroup$
              Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
              $endgroup$
              – amd
              Jan 4 at 4:47
















            0












            $begingroup$

            You can determine the "type" of the critical point using the partial derivatives. Suppose $(x,y)$ is a critical point that you are considering. Then,




            1. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} > 0$ when evaluated at $(x,y)$, then there is a relative minimum at $(x,y)$.

            2. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} < 0$, you have a relative minimum.

            3. If $f_{xx} f_{yy}- (f_{xx})^2 < 0$ then you've got a saddle point.

            4. If $f_{xx} f_{yy}- (f_{xx})^2 = 0$ its indeterminate.


            Edit: Just looked at the function you've provided. Clearly, it's going to indeterminate since the second derivative for $x$ or $y$ is $0$. You'll have to just plug in the values of the critical points you've found and determine it based on that.






            share|cite|improve this answer









            $endgroup$









            • 1




              $begingroup$
              This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
              $endgroup$
              – Will M.
              Jan 4 at 4:36






            • 1




              $begingroup$
              Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
              $endgroup$
              – amd
              Jan 4 at 4:47














            0












            0








            0





            $begingroup$

            You can determine the "type" of the critical point using the partial derivatives. Suppose $(x,y)$ is a critical point that you are considering. Then,




            1. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} > 0$ when evaluated at $(x,y)$, then there is a relative minimum at $(x,y)$.

            2. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} < 0$, you have a relative minimum.

            3. If $f_{xx} f_{yy}- (f_{xx})^2 < 0$ then you've got a saddle point.

            4. If $f_{xx} f_{yy}- (f_{xx})^2 = 0$ its indeterminate.


            Edit: Just looked at the function you've provided. Clearly, it's going to indeterminate since the second derivative for $x$ or $y$ is $0$. You'll have to just plug in the values of the critical points you've found and determine it based on that.






            share|cite|improve this answer









            $endgroup$



            You can determine the "type" of the critical point using the partial derivatives. Suppose $(x,y)$ is a critical point that you are considering. Then,




            1. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} > 0$ when evaluated at $(x,y)$, then there is a relative minimum at $(x,y)$.

            2. If $f_{xx} f_{yy}- (f_{xx})^2 > 0$ and $f_{xx} < 0$, you have a relative minimum.

            3. If $f_{xx} f_{yy}- (f_{xx})^2 < 0$ then you've got a saddle point.

            4. If $f_{xx} f_{yy}- (f_{xx})^2 = 0$ its indeterminate.


            Edit: Just looked at the function you've provided. Clearly, it's going to indeterminate since the second derivative for $x$ or $y$ is $0$. You'll have to just plug in the values of the critical points you've found and determine it based on that.







            share|cite|improve this answer












            share|cite|improve this answer



            share|cite|improve this answer










            answered Jan 4 at 4:13









            kkckkc

            1199




            1199








            • 1




              $begingroup$
              This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
              $endgroup$
              – Will M.
              Jan 4 at 4:36






            • 1




              $begingroup$
              Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
              $endgroup$
              – amd
              Jan 4 at 4:47














            • 1




              $begingroup$
              This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
              $endgroup$
              – Will M.
              Jan 4 at 4:36






            • 1




              $begingroup$
              Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
              $endgroup$
              – amd
              Jan 4 at 4:47








            1




            1




            $begingroup$
            This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
            $endgroup$
            – Will M.
            Jan 4 at 4:36




            $begingroup$
            This only provides local maxima or minima of the restricted function. For global one uses compactness and this criterion is then useless.
            $endgroup$
            – Will M.
            Jan 4 at 4:36




            1




            1




            $begingroup$
            Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
            $endgroup$
            – amd
            Jan 4 at 4:47




            $begingroup$
            Examining the Jacobian determinant of the objective function in a constrained optimization problem doesn’t usually tell you anything useful. This problem is a case in point: the Jacobian determinant is identically equal to $-9$, so per these criteria the only critical points are saddle points. This is true of $f$ on $mathbb R^2$, but certainly not of its restriction to the ellipse.
            $endgroup$
            – amd
            Jan 4 at 4:47


















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