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MATH1251 Questions HELP (2 Viewers)

InteGrand

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(a) Using the notation in the suggestion provided, I get a'(x) = 1-2x and b'(x) = 2y.

If I then set these to equal 0, I get x = 1/2 and y = 0. I also used parts of my original approach to determine the other critical points. However, none of these provide the maximum value that is provided in the answers, at the point (1/2, 2) = 17/4, while the maximum I get is at (0,2) = 4. However, my minimas match.

(b) Sorry, but I have no idea how to approach this one...
Note for a), you just need to maximise and minimise x - x^2 for x in [0, 3] and maximise and minimise y^2 for y in [0,2] (the latter obviously has min. value 0 and max. value 4, no real calculations needed). Add the max. values to get f(x,y)'s max. and add the min. values to get the min.

When you found the stationary points of a(x) and b(y), the stat. point for a(x) was a max., but for b(y) was a min. So adding these isn't helpful, since we need to add min's and add max's.
 
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InteGrand

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(a) Using the notation in the suggestion provided, I get a'(x) = 1-2x and b'(x) = 2y.

If I then set these to equal 0, I get x = 1/2 and y = 0. I also used parts of my original approach to determine the other critical points. However, none of these provide the maximum value that is provided in the answers, at the point (1/2, 2) = 17/4, while the maximum I get is at (0,2) = 4. However, my minimas match.

(b) Sorry, but I have no idea how to approach this one...




 
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leehuan

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It was easy to state that:
a) x^2+y^2 ---> local min
b) x^4-y^4 ---> saddle

 

leehuan

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(x+3y)(x+y)=z

it's an oblique oriented sheet with parabolic cross-section.
Didn't fully understand that oblique sheet language. (We didn't really name multivariable curves.)

That being said though, for a) and b) I just limited x->0 and y->0 separately. I kinda had a feeling it wouldn't work here due to the xy but I don't know how to justify it.
 

Paradoxica

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Didn't fully understand that oblique sheet language. (We didn't really name multivariable curves.)

That being said though, for a) and b) I just limited x->0 and y->0 separately. I kinda had a feeling it wouldn't work here due to the xy but I don't know how to justify it.
It's a special case, I think. The function is constant along one line, but convex, so it's somewhere between a stationary point and a saddle point.
 

leehuan

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Ah so basically try to find some condition between x and y so that we can prove it's a min in one plane and a max in the other?

Awesome makes sense. Do we just have to guess something like x=-2y that would work?
 

InteGrand

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Ah so basically try to find some condition between x and y so that we can prove it's a min in one plane and a max in the other?

Awesome makes sense. Do we just have to guess something like x=-2y that would work?
 

leehuan

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When doing these questions regarding max min for multivariable functions, would we be safe to just ignore any saddle points we come across?
Thanks for clarifying!

This time from Algebra:
Parts (b) and (c) of this one please
Hint for part b): Expand that thing out first before you use the roots of unity sum (GP)
 

leehuan

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With those questions already posted, could they be done using Lagrange multipliers in a more quicker way? Or is that a meh choice because you still have to split up the cases
 

seanieg89

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Lagrange multipliers is how you deal with constrained optimisation problems. I.e. when you are optimising a function f on a hypersurface in R^n rather than on R^n itself.

In this case however, we were optimising a function over a domain in R^n. You can optimise the function in the interior of such domains by looking at stationary points and using higher derivative tests.

To look at what the function does on the boundary, you can either locally parametrise the boundary to reduce it to a lower dimensional interior optimisation problem of the type above, or you can use Lagrange multipliers, but this is messier. The main strength of Lagrange multipliers is that we can use it to deal with implicitly defined hypersurfaces that are not easy to parametrise.

In the problem above where we optimised over a triangle, the method I hinted at and Integrand fleshed out involved writing the triangle as a union of hypersurfaces. Indeed we could use Lagrange multipliers to optimise over the individual hypersurfaces, but the whole point of the decomposition was that the function took a very simple form on the hypersurfaces and was easy to optimise with just AM-GM. Otherwise there would be no point in decomposing the domain in this way and one would just optimise over the interior and boundary points as described above.
 

leehuan

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Oh right right, my bad.


Anyway, on the note of Lagrange multipliers



So from the theorem I arrived at the points


All I want to know is what's the quickest way to finish of the question to deduce an answer?

Do we just evaluate f(x,y) (where f(x)=x^2+y^2) and just inspect the answer from there? Or did I forget something.
 

InteGrand

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Oh right right, my bad.


Anyway, on the note of Lagrange multipliers



So from the theorem I arrived at the points


All I want to know is what's the quickest way to finish of the question to deduce an answer?

Do we just evaluate f(x,y) (where f(x)=x^2+y^2) and just inspect the answer from there? Or did I forget something.
Once we have the candidate points, yeah, just evaluate the function at them to find the maximum and minimum. (In this case we're optimising a continuous function over a compact domain, so we're guaranteed a global maximum and a minimum value on this domain.)
 

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Oh right right, my bad.


Anyway, on the note of Lagrange multipliers



So from the theorem I arrived at the points


All I want to know is what's the quickest way to finish of the question to deduce an answer?

Do we just evaluate f(x,y) (where f(x)=x^2+y^2) and just inspect the answer from there? Or did I forget something.
I used AM-GM to arrive at xy = 2/3 in order for a minimum to occur. Only the second satisfies that condition, so it must be the minimum.
 

leehuan

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Use double integration to find the area of the region bounded by y=x^3 and y=x^2

Just set up the integral please
 

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