MIT-OCW-Transcripts / -CsEPYeSBsg.txt
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welcome back to recitation today we're
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welcome back to recitation today we're
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welcome back to recitation today we're
going to work on an optimization problem
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going to work on an optimization problem
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going to work on an optimization problem
so the question I want us to answer is
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so the question I want us to answer is
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so the question I want us to answer is
what point on the curve y equals square
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what point on the curve y equals square
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what point on the curve y equals square
root of X+ 4 comes closest to the origin
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root of X+ 4 comes closest to the origin
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root of X+ 4 comes closest to the origin
I've drawn a sketch of this curve the
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I've drawn a sketch of this curve the
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I've drawn a sketch of this curve the
scale in this direction the each hash
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scale in this direction the each hash
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scale in this direction the each hash
mark is one unit in the X Direction each
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mark is one unit in the X Direction each
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mark is one unit in the X Direction each
hash mark here is one unit in the y
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hash mark here is one unit in the y
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hash mark here is one unit in the y
direction just want to point out two
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direction just want to point out two
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direction just want to point out two
easy places to figure out the distance
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easy places to figure out the distance
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easy places to figure out the distance
to the origin over here where the curve
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to the origin over here where the curve
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to the origin over here where the curve
starts at40 the distance to the origin
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starts at40 the distance to the origin
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starts at40 the distance to the origin
is 4 units and here at 02 the distance
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is 4 units and here at 02 the distance
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is 4 units and here at 02 the distance
of the origin is two units so probably
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of the origin is two units so probably
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of the origin is two units so probably
we could safely say further away here so
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we could safely say further away here so
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we could safely say further away here so
we're anticipating that somewhere along
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we're anticipating that somewhere along
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we're anticipating that somewhere along
the curve in this region is where we
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the curve in this region is where we
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the curve in this region is where we
should find our our place that's closest
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should find our our place that's closest
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should find our our place that's closest
to the origin the only reason I point
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to the origin the only reason I point
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to the origin the only reason I point
that out is that when you're doing these
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that out is that when you're doing these
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that out is that when you're doing these
problems on your own you should always
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problems on your own you should always
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problems on your own you should always
try and anticipate roughly where thing
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try and anticipate roughly where thing
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try and anticipate roughly where thing
should happen in what kind of region so
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should happen in what kind of region so
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should happen in what kind of region so
that you don't you don't start thinking
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that you don't you don't start thinking
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that you don't you don't start thinking
if you if you do something wrong and you
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if you if you do something wrong and you
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if you if you do something wrong and you
get x equals 100 and then you come back
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get x equals 100 and then you come back
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get x equals 100 and then you come back
and look at the curve you realize right
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and look at the curve you realize right
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and look at the curve you realize right
away well that doesn't make any sense so
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away well that doesn't make any sense so
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away well that doesn't make any sense so
we would always be thinking as we're
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we would always be thinking as we're
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we would always be thinking as we're
solving the problem does my answer make
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solving the problem does my answer make
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solving the problem does my answer make
sense so I'm actually going to give you
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sense so I'm actually going to give you
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sense so I'm actually going to give you
a little bit of time to work on this
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a little bit of time to work on this
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a little bit of time to work on this
yourself and then I'll come back and
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yourself and then I'll come back and
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yourself and then I'll come back and
I'll work on it as
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well well welcome back hopefully you
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well well welcome back hopefully you
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well well welcome back hopefully you
were able to get pretty far into this
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were able to get pretty far into this
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were able to get pretty far into this
problem and so I will start working on
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problem and so I will start working on
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problem and so I will start working on
it
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it
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it
now so the again the question is that we
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now so the again the question is that we
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now so the again the question is that we
want to we want to optimize uh in this
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want to we want to optimize uh in this
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want to we want to optimize uh in this
in this case minimize distance to the
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in this case minimize distance to the
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in this case minimize distance to the
origin from this curve and so what we're
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origin from this curve and so what we're
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origin from this curve and so what we're
really trying to do is we have we have a
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really trying to do is we have we have a
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really trying to do is we have we have a
constraint the constraint is we have to
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constraint the constraint is we have to
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constraint the constraint is we have to
be on the curve and then we also have um
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be on the curve and then we also have um
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be on the curve and then we also have um
something we're trying to minimize and
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something we're trying to minimize and
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something we're trying to minimize and
the thing we're trying to minimize is
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the thing we're trying to minimize is
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the thing we're trying to minimize is
distance and so we have to we have to
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distance and so we have to we have to
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distance and so we have to we have to
make sure that we understand the two
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make sure that we understand the two
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make sure that we understand the two
equations that we need the optimization
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equations that we need the optimization
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equations that we need the optimization
or the constraint equation and the
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or the constraint equation and the
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or the constraint equation and the
optimizing equation so to optimize we
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optimizing equation so to optimize we
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optimizing equation so to optimize we
need to know how to measure distance in
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need to know how to measure distance in
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need to know how to measure distance in
in two-dimensional space and one point I
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in two-dimensional space and one point I
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in two-dimensional space and one point I
want to make is that if you want to
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want to make is that if you want to
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want to make is that if you want to
optimize distance you might as well
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optimize distance you might as well
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optimize distance you might as well
optimize the square of distance because
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optimize the square of distance because
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optimize the square of distance because
it's much easier so let me justify that
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it's much easier so let me justify that
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it's much easier so let me justify that
briefly and then we'll go on so I want
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briefly and then we'll go on so I want
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briefly and then we'll go on so I want
to optimize the distance squared to the
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to optimize the distance squared to the
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to optimize the distance squared to the
origin it's well distance you remember
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origin it's well distance you remember
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origin it's well distance you remember
first in general between two points x y
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first in general between two points x y
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first in general between two points x y
and ab is is something in this
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and ab is is something in this
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and ab is is something in this
form distance squared is the difference
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form distance squared is the difference
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form distance squared is the difference
between the x value squared plus the
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between the x value squared plus the
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between the x value squared plus the
difference between the y- value squared
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difference between the y- value squared
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difference between the y- value squared
this is should remind you of the
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this is should remind you of the
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this is should remind you of the
Pythagorean theorem
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Pythagorean theorem
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Pythagorean theorem
ultimately so in this case in our case
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ultimately so in this case in our case
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ultimately so in this case in our case
distance is to the origin is x^2 + y^2
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distance is to the origin is x^2 + y^2
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distance is to the origin is x^2 + y^2
the distance squ is x2+ y^2 I just told
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the distance squ is x2+ y^2 I just told
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the distance squ is x2+ y^2 I just told
you that instead of trying to optimize
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you that instead of trying to optimize
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you that instead of trying to optimize
distance we can optimize distance
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distance we can optimize distance
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distance we can optimize distance
squared Why is that well remember that
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squared Why is that well remember that
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squared Why is that well remember that
when you optimize what you're looking
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when you optimize what you're looking
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when you optimize what you're looking
for is a place where the derivative of
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for is a place where the derivative of
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for is a place where the derivative of
the function of of interest is equal to
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the function of of interest is equal to
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the function of of interest is equal to
zero so what I want to point out is that
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zero so what I want to point out is that
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zero so what I want to point out is that
when you take the derivative of distance
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when you take the derivative of distance
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when you take the derivative of distance
squared and find where that's zero it's
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squared and find where that's zero it's
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squared and find where that's zero it's
going to be the same as the place where
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going to be the same as the place where
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going to be the same as the place where
uh where the derivative of distance is
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uh where the derivative of distance is
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uh where the derivative of distance is
equal to zero so let's notice that so
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equal to zero so let's notice that so
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equal to zero so let's notice that so
this is a little
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this is a little
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this is a little
sidebar
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justification notice d squ Prime is
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justification notice d squ Prime is
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justification notice d squ Prime is
equal to 2D D Prime where did that come
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equal to 2D D Prime where did that come
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equal to 2D D Prime where did that come
from that's this is implicit
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from that's this is implicit
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from that's this is implicit
differentiation with respect to X and
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differentiation with respect to X and
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differentiation with respect to X and
this is the chain rule so if I want D
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this is the chain rule so if I want D
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this is the chain rule so if I want D
Prime to equal zero I can also find
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Prime to equal zero I can also find
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Prime to equal zero I can also find
where D2 Prime equals zero I'm assuming
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where D2 Prime equals zero I'm assuming
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where D2 Prime equals zero I'm assuming
notice the distance is never at the
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notice the distance is never at the
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notice the distance is never at the
origin so distance is never zero so I
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origin so distance is never zero so I
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origin so distance is never zero so I
don't have to worry about that so that's
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don't have to worry about that so that's
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don't have to worry about that so that's
a small sidebar but just to justify why
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a small sidebar but just to justify why
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a small sidebar but just to justify why
we can do that now let's come back into
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we can do that now let's come back into
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we can do that now let's come back into
the problem at hand what is our
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the problem at hand what is our
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the problem at hand what is our
optimization problem um
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optimization problem um
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optimization problem um
equation that we want to minimize we
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equation that we want to minimize we
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equation that we want to minimize we
want to minimize this
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want to minimize this
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want to minimize this
equation with respect to a certain
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equation with respect to a certain
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equation with respect to a certain
constraint what's the constraint the
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constraint what's the constraint the
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constraint what's the constraint the
constraint is what Y is y depends on on
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constraint is what Y is y depends on on
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constraint is what Y is y depends on on
X and so when I solve these problems I'm
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X and so when I solve these problems I'm
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X and so when I solve these problems I'm
I'm going to have to substitute in my
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I'm going to have to substitute in my
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I'm going to have to substitute in my
constraint so y^2 is the square root of
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constraint so y^2 is the square root of
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constraint so y^2 is the square root of
X+ 4 quantity squared so I just get X+
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X+ 4 quantity squared so I just get X+
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X+ 4 quantity squared so I just get X+
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so now I have my optimization equation
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so now I have my optimization equation
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so now I have my optimization equation
how do I find a minimum or a maximum I
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how do I find a minimum or a maximum I
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how do I find a minimum or a maximum I
take the derivative and set it equal to
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take the derivative and set it equal to
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take the derivative and set it equal to
zero so let me come give myself a little
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zero so let me come give myself a little
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zero so let me come give myself a little
more room and do that over
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more room and do that over
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more room and do that over
here so d^2
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here so d^2
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here so d^2
Prime now I get derivative of X2 is
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Prime now I get derivative of X2 is
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Prime now I get derivative of X2 is
2x the derivative of x is one and the
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2x the derivative of x is one and the
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2x the derivative of x is one and the
derivative of four is zero this will be
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derivative of four is zero this will be
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derivative of four is zero this will be
optimized when this is equal Al to 0 so
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optimized when this is equal Al to 0 so
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optimized when this is equal Al to 0 so
0 = 2x + 1 so X is equal to
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-2 does this pass as we would say maybe
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-2 does this pass as we would say maybe
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-2 does this pass as we would say maybe
the smell test does it smell okay to us
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the smell test does it smell okay to us
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the smell test does it smell okay to us
the answer will be yes because it
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the answer will be yes because it
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the answer will be yes because it
remember we said somewhere in this x
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remember we said somewhere in this x
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remember we said somewhere in this x
region is where we expect that we will
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region is where we expect that we will
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region is where we expect that we will
have a distance closest a point closest
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have a distance closest a point closest
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have a distance closest a point closest
to the origin and so we're right here on
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to the origin and so we're right here on
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to the origin and so we're right here on
the x value now we have to find what the
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the x value now we have to find what the
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the x value now we have to find what the
Y value is to finish the problem but
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Y value is to finish the problem but
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Y value is to finish the problem but
this this is not so far very surprising
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this this is not so far very surprising
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this this is not so far very surprising
it seems like maybe the right thing now
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it seems like maybe the right thing now
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it seems like maybe the right thing now
we have X so now how do we find y well
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we have X so now how do we find y well
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we have X so now how do we find y well
we know what Y is y is equal to the
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we know what Y is y is equal to the
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we know what Y is y is equal to the
square root of x + 4 so it's equal to
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square root of x + 4 so it's equal to
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square root of x + 4 so it's equal to
theun of -2 +
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theun of -2 +
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theun of -2 +
4 which simplified is three and a half
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4 which simplified is three and a half
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4 which simplified is three and a half
which I think uh is seven
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which I think uh is seven
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which I think uh is seven
halves so the point is -
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halves so the point is -
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halves so the point is -
one2 comma square root of
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one2 comma square root of
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one2 comma square root of
sevenes and then you just want to double
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sevenes and then you just want to double
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sevenes and then you just want to double
check and make sure did I ask for the
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check and make sure did I ask for the
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check and make sure did I ask for the
distance or did I ask for the point and
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distance or did I ask for the point and
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distance or did I ask for the point and
right now we have the point so let's
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right now we have the point so let's
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right now we have the point so let's
come over and make sure what point on
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come over and make sure what point on
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come over and make sure what point on
the curve is comes closest to the origin
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the curve is comes closest to the origin
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the curve is comes closest to the origin
so now we know that we've answered the
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so now we know that we've answered the
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so now we know that we've answered the
correct question so again it was a maxim
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correct question so again it was a maxim
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correct question so again it was a maxim
maximize Min sorry it was a minimizing
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maximize Min sorry it was a minimizing
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maximize Min sorry it was a minimizing
problem it was an optimization problem
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problem it was an optimization problem
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problem it was an optimization problem
where we wanted to minimize distance we
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where we wanted to minimize distance we
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where we wanted to minimize distance we
had a constraint equation we had the
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had a constraint equation we had the
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had a constraint equation we had the
thing we wanted to minimize then we took
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thing we wanted to minimize then we took
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thing we wanted to minimize then we took
the derivative of the minimizer set it
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the derivative of the minimizer set it
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the derivative of the minimizer set it
or of the optimizing equation set it
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or of the optimizing equation set it
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or of the optimizing equation set it
equal to zero solved for x and then
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equal to zero solved for x and then
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equal to zero solved for x and then
found the answer to the specific
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found the answer to the specific
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found the answer to the specific
question by then finding the Y value and
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question by then finding the Y value and
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question by then finding the Y value and
I think I'll stop there