Optimization problems are just max/min problems with some additional reading comprehension.
Same content as the slide version, but laid out three to a page with space for notes.
Two non-traditional content courses for in-service high school teachers at th...Matthew Leingang
We describe the Harvard Extension School's ALM in Mathematics for Teaching program and in detail two courses taught in an inquiry-based learning (IBL) style
Two non-traditional content courses for in-service high school teachers at th...Matthew Leingang
We describe the Harvard Extension School's ALM in Mathematics for Teaching program and in detail two courses taught in an inquiry-based learning (IBL) style
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
At times it is useful to consider a function whose derivative is a given function. We look at the general idea of reversing the differentiation process and its applications to rectilinear motion.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Lesson 12: Linear Approximation and Differentials (Section 21 slides)Mel Anthony Pepito
The line tangent to a curve is also the line which best "fits" the curve near that point. So derivatives can be used for approximating complicated functions with simple linear ones. Differentials are another set of notation for the same problem.
Lesson 12: Linear Approximation and Differentials (Section 21 slides)Matthew Leingang
The line tangent to a curve is also the line which best "fits" the curve near that point. So derivatives can be used for approximating complicated functions with simple linear ones. Differentials are another set of notation for the same problem.
Lesson 9: The Product and Quotient Rules (Section 21 slides)Mel Anthony Pepito
The derivative of a sum of functions is the sum of the derivatives of those functions, but the derivative of a product or a quotient of functions is not so simple. We'll derive and use the product and quotient rule for these purposes. It will allow us to find the derivatives of other trigonometric functions, and derivatives of power functions with negative whole number exponents.
Lesson 9: The Product and Quotient Rules (Section 21 slides)Matthew Leingang
The derivative of a sum of functions is the sum of the derivatives of those functions, but the derivative of a product or a quotient of functions is not so simple. We'll derive and use the product and quotient rule for these purposes. It will allow us to find the derivatives of other trigonometric functions, and derivatives of power functions with negative whole number exponents.
We trace the computation of area through the centuries. The process known known as Riemann Sums has applications to not just area but many fields of science.
(Handout version of slideshow from class)
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Streamlining assessment, feedback, and archival with auto-multiple-choiceMatthew Leingang
Auto-multiple-choice (AMC) is an open-source optical mark recognition software package built with Perl, LaTeX, XML, and sqlite. I use it for all my in-class quizzes and exams. Unique papers are created for each student, fixed-response items are scored automatically, and free-response problems, after manual scoring, have marks recorded in the same process. In the first part of the talk I will discuss AMC’s many features and why I feel it’s ideal for a mathematics course. My contributions to the AMC workflow include some scripts designed to automate the process of returning scored papers
back to students electronically. AMC provides an email gateway, but I have written programs to return graded papers via the DAV protocol to student’s dropboxes on our (Sakai) learning management systems. I will also show how graded papers can be archived, with appropriate metadata tags, into an Evernote notebook.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
At times it is useful to consider a function whose derivative is a given function. We look at the general idea of reversing the differentiation process and its applications to rectilinear motion.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Lesson 12: Linear Approximation and Differentials (Section 21 slides)Mel Anthony Pepito
The line tangent to a curve is also the line which best "fits" the curve near that point. So derivatives can be used for approximating complicated functions with simple linear ones. Differentials are another set of notation for the same problem.
Lesson 12: Linear Approximation and Differentials (Section 21 slides)Matthew Leingang
The line tangent to a curve is also the line which best "fits" the curve near that point. So derivatives can be used for approximating complicated functions with simple linear ones. Differentials are another set of notation for the same problem.
Lesson 9: The Product and Quotient Rules (Section 21 slides)Mel Anthony Pepito
The derivative of a sum of functions is the sum of the derivatives of those functions, but the derivative of a product or a quotient of functions is not so simple. We'll derive and use the product and quotient rule for these purposes. It will allow us to find the derivatives of other trigonometric functions, and derivatives of power functions with negative whole number exponents.
Lesson 9: The Product and Quotient Rules (Section 21 slides)Matthew Leingang
The derivative of a sum of functions is the sum of the derivatives of those functions, but the derivative of a product or a quotient of functions is not so simple. We'll derive and use the product and quotient rule for these purposes. It will allow us to find the derivatives of other trigonometric functions, and derivatives of power functions with negative whole number exponents.
We trace the computation of area through the centuries. The process known known as Riemann Sums has applications to not just area but many fields of science.
(Handout version of slideshow from class)
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
Streamlining assessment, feedback, and archival with auto-multiple-choiceMatthew Leingang
Auto-multiple-choice (AMC) is an open-source optical mark recognition software package built with Perl, LaTeX, XML, and sqlite. I use it for all my in-class quizzes and exams. Unique papers are created for each student, fixed-response items are scored automatically, and free-response problems, after manual scoring, have marks recorded in the same process. In the first part of the talk I will discuss AMC’s many features and why I feel it’s ideal for a mathematics course. My contributions to the AMC workflow include some scripts designed to automate the process of returning scored papers
back to students electronically. AMC provides an email gateway, but I have written programs to return graded papers via the DAV protocol to student’s dropboxes on our (Sakai) learning management systems. I will also show how graded papers can be archived, with appropriate metadata tags, into an Evernote notebook.
Integration by substitution is the chain rule in reverse.
NOTE: the final location is section specific. Section 1 (morning) is in SILV 703, Section 11 (afternoon) is in CANT 200
Lesson 24: Areas and Distances, The Definite Integral (handout)Matthew Leingang
We can define the area of a curved region by a process similar to that by which we determined the slope of a curve: approximation by what we know and a limit.
Lesson 24: Areas and Distances, The Definite Integral (slides)Matthew Leingang
We can define the area of a curved region by a process similar to that by which we determined the slope of a curve: approximation by what we know and a limit.
At times it is useful to consider a function whose derivative is a given function. We look at the general idea of reversing the differentiation process and its applications to rectilinear motion.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
The Mean Value Theorem is the most important theorem in calculus. It is the first theorem which allows us to infer information about a function from information about its derivative. From the MVT we can derive tests for the monotonicity (increase or decrease) and concavity of a function.
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
1. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Notes
Section 4.5
Optimization Problems
V63.0121.006/016, Calculus I
New York University
April 7, 2010
Announcements
Thank you for the evaluations
Quiz 4 April 16 on §§4.1–4.4
Announcements
Notes
Thank you for the evaluations
Quiz 4 April 16 on §§4.1–4.4
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 2 / 36
Evaluations: The good
Notes
“Very knowledgeable”
“Knows how to teach”
“Very good at projecting voice”
“Office hours are accessible”
“Clean”
“Great syllabus”
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 3 / 36
1
2. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Evaluations: The bad
Notes
Too fast, not enough examples
Not enough time to do everything
Lecture is not the only learning time (recitation and independent study)
I try to balance concept and procedure
Too many proofs
In this course we care about concepts
There will be conceptual problems on the exam
Concepts are the keys to overcoming templated problems
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 4 / 36
Evaluations: The ugly
Notes
“The projector blows.”
“Sometimes condescending/rude.”
“Can’t pick his nose without checking his notes, and he still gets it
wrong the first time.”
“If I were chained to a desk and forced to see this guy teach, I would
chew my arm off in order to get free.”
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 5 / 36
A slide on slides
Notes
Pro
“Excellent slides and examples”
“clear and well-rehearsed”
“Slides are easy to follow and posted”
Con
“I wish he would actually use the chalkboard occasionally”
“Sometimes the slides skip steps”
“too fast”
Why I like them
Board handwriting not an issue
Easy to put online; notetaking is more than transcription
What we can do
if you have suggestions for details to put in, I’m listening
Feel free to ask me to fill in something on the board
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 6 / 36
2
3. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
My handwriting
Notes
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 7 / 36
A slide on slides
Notes
Pro
“Excellent slides and examples”
“clear and well-rehearsed”
“Slides are easy to follow and posted”
Con
“I wish he would actually use the chalkboard occasionally”
“Sometimes the slides skip steps”
“too fast”
Why I like them
Board handwriting not an issue
Easy to put online; notetaking is more than transcription
What we can do
if you have suggestions for details to put in, I’m listening
Feel free to ask me to fill in something on the board
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 8 / 36
Leading by Example
Notes
Example
What is the rectangle of fixed perimeter with maximum area?
Solution
Draw a rectangle.
w
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 10 / 36
3
4. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Solution Continued
Notes
Let its length be and its width be w . The objective function is area
A = w.
This is a function of two variables, not one. But the perimeter is fixed.
p − 2w
Since p = 2 + 2w , we have = , so
2
p − 2w 1 1
A= w = · w = (p − 2w )(w ) = pw − w 2
2 2 2
Now we have A as a function of w alone (p is constant).
The natural domain of this function is [0, p/2] (we want to make sure
A(w ) ≥ 0).
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 11 / 36
Solution Concluded
Notes
1
We use the Closed Interval Method for A(w ) = pw − w 2 on [0, p/2].
2
At the endpoints, A(0) = A(p/2) = 0.
dA 1
To find the critical points, we find = p − 2w .
dw 2
The critical points are when
1 p
0 = p − 2w =⇒ w =
2 4
Since this is the only critical point, it must be the maximum. In this
p
case = as well.
4
We have a square! The maximal area is A(p/4) = p 2 /16.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 12 / 36
Strategies for Problem Solving
Notes
1. Understand the problem
2. Devise a plan
3. Carry out the plan
4. Review and extend
Gy¨rgy P´lya
o o
(Hungarian, 1887–1985)
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 14 / 36
4
5. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
The Text in the Box
Notes
1. Understand the Problem. What is known? What is unknown?
What are the conditions?
2. Draw a diagram.
3. Introduce Notation.
4. Express the “objective function” Q in terms of the other symbols
5. If Q is a function of more than one “decision variable”, use the given
information to eliminate all but one of them.
6. Find the absolute maximum (or minimum, depending on the problem)
of the function on its domain.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 15 / 36
Name [_
Problem Solving Strategy
Draw a Picture Notes
Kathy had a box of 8 crayons.
She gave some crayons away.
She has 5 left.
How many crayons did Kathy give away?
UNDERSTAND
•
What do you want to find out?
Draw a line under the question.
You can draw a picture
to solve the problem.
What number do I
add to 5 to get 8?
8 - = 5
crayons 5 + 3 = 8
CHECK
Does your answer make sense?
Explain.
What number
Draw a picture to solve the problem. do I add to 3
Write how many were given away. to make 10?
I. I had 10 pencils. ft ft ft A
I gave some away. 13 ill
i :i
I
'•' I I
I have 3 left. How many i? «
11 I
pencils did I give away? I
H 11
M i l
~7 U U U U> U U
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 16 / 36
Recall: The Closed Interval Method
See Section 4.1 Notes
To find the extreme values of a function f on [a, b], we need to:
Evaluate f at the endpoints a and b
Evaluate f at the critical points x where either f (x) = 0 or f is not
differentiable at x.
The points with the largest function value are the global maximum
points
The points with the smallest or most negative function value are the
global minimum points.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 17 / 36
5
6. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Recall: The First Derivative Test
See Section 4.3 Notes
Theorem (The First Derivative Test)
Let f be continuous on [a, b] and c a critical point of f in (a, b).
If f changes from negative to positive at c, then c is a local
minimum.
If f changes from positive to negative at c, then c is a local
maximum.
If f does not change sign at c, then c is not a local extremum.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 18 / 36
Recall: The Second Derivative Test
See Section 4.3 Notes
Theorem (The Second Derivative Test)
Let f , f , and f be continuous on [a, b]. Let c be be a point in (a, b)
with f (c) = 0.
If f (c) < 0, then f (c) is a local maximum.
If f (c) > 0, then f (c) is a local minimum.
Warning
If f (c) = 0, the second derivative test is inconclusive (this does not mean
c is neither; we just don’t know yet).
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 19 / 36
Which to use when?
Notes
CIM 1DT 2DT
Pro – no need for – works on – works on
inequalities non-closed, non-closed,
– gets global extrema non-bounded non-bounded
automatically intervals intervals
– only one derivative – no need for
inequalities
Con – only for closed – Uses inequalities – More derivatives
bounded intervals – More work at – less conclusive than
boundary than CIM 1DT
– more work at
boundary than CIM
Use CIM if it applies: the domain is a closed, bounded interval
If domain is not closed or not bounded, use 2DT if you like to take
derivatives, or 1DT if you like to compare signs.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 20 / 36
6
7. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Another Example
Notes
Example (The Best Fencing Plan)
A rectangular plot of farmland will be bounded on one side by a river and
on the other three sides by a single-strand electric fence. With 800m of
wire at your disposal, what is the largest area you can enclose, and what
are its dimensions?
Known: amount of fence used
Unknown: area enclosed
Objective: maximize area
Constraint: fixed fence length
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 22 / 36
Solution
Notes
1. Everybody understand?
2. Draw a diagram.
3. Length and width are and w . Length of wire used is p.
4. Q = area = w .
5. Since p = + 2w , we have = p − 2w and so
Q(w ) = (p − 2w )(w ) = pw − 2w 2
The domain of Q is [0, p/2]
dQ p
6. = p − 4w , which is zero when w = . Q(0) = Q(p/2) = 0, but
dw 4
p p p2 p2
Q =p· −2· = = 80, 000m2
4 4 16 8
so the critical point is the absolute maximum.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 23 / 36
Another Example
Notes
Example (The Best Fencing Plan)
A rectangular plot of farmland will be bounded on one side by a river and
on the other three sides by a single-strand electric fence. With 800m of
wire at your disposal, what is the largest area you can enclose, and what
are its dimensions?
Known: amount of fence used
Unknown: area enclosed
Objective: maximize area
Constraint: fixed fence length
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 24 / 36
7
8. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Solution
Notes
1. Everybody understand?
2. Draw a diagram.
3. Length and width are and w . Length of wire used is p.
4. Q = area = w .
5. Since p = + 2w , we have = p − 2w and so
Q(w ) = (p − 2w )(w ) = pw − 2w 2
The domain of Q is [0, p/2]
dQ p
6. = p − 4w , which is zero when w = . Q(0) = Q(p/2) = 0, but
dw 4
p p p2 p2
Q =p· −2· = = 80, 000m2
4 4 16 8
so the critical point is the absolute maximum.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 25 / 36
Diagram
Notes
A rectangular plot of farmland will be bounded on one side by a river and
on the other three sides by a single-strand electric fence. With 800 m of
wire at your disposal, what is the largest area you can enclose, and what
are its dimensions?
w
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 26 / 36
Solution
Notes
1. Everybody understand?
2. Draw a diagram.
3. Length and width are and w . Length of wire used is p.
4. Q = area = w .
5. Since p = + 2w , we have = p − 2w and so
Q(w ) = (p − 2w )(w ) = pw − 2w 2
The domain of Q is [0, p/2]
dQ p
6. = p − 4w , which is zero when w = . Q(0) = Q(p/2) = 0, but
dw 4
p p p2 p2
Q =p· −2· = = 80, 000m2
4 4 16 8
so the critical point is the absolute maximum.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 27 / 36
8
9. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Diagram
Notes
A rectangular plot of farmland will be bounded on one side by a river and
on the other three sides by a single-strand electric fence. With 800 m of
wire at your disposal, what is the largest area you can enclose, and what
are its dimensions?
w
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 28 / 36
Solution
Notes
1. Everybody understand?
2. Draw a diagram.
3. Length and width are and w . Length of wire used is p.
4. Q = area = w .
5. Since p = + 2w , we have = p − 2w and so
Q(w ) = (p − 2w )(w ) = pw − 2w 2
The domain of Q is [0, p/2]
dQ p
6. = p − 4w , which is zero when w = . Q(0) = Q(p/2) = 0, but
dw 4
p p p2 p2
Q =p· −2· = = 80, 000m2
4 4 16 8
so the critical point is the absolute maximum.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 29 / 36
Your turn
Notes
Example (The shortest fence)
A 216m2 rectangular pea patch is to be enclosed by a fence and divided
into two equal parts by another fence parallel to one of its sides. What
dimensions for the outer rectangle will require the smallest total length of
fence? How much fence will be needed?
Solution
Let the length and width of the pea patch be and w . The amount of
fence needed is f = 2 + 3w . Since w = A, a constant, we have
A
f (w ) = 2 + 3w .
w
The domain is all positive numbers.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 30 / 36
9
10. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Diagram
Notes
w
f = 2 + 3w A = w ≡ 216
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 31 / 36
Solution (Continued)
2A Notes
We need to find the minimum value of f (w ) = + 3w on (0, ∞).
w
We have
df 2A
=− 2 +3
dw w
2A
which is zero when w = .
3
−3
Since f (w ) = 4Aw , which is positive for all positive w , the critical
point is a minimum, in fact the global minimum.
2A
So the area is minimized when w = = 12 and
3
A 3A
= = = 18. The amount of fence needed is
w 2
2A 3A 2A √ √
f =2· +3 = 2 6A = 2 6 · 216 = 72m
3 2 3
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 32 / 36
Try this one
Notes
Example
An advertisement consists of a rectangular printed region plus 1 in margins
on the sides and 1.5 in margins on the top and bottom. If the total area of
the advertisement is to be 120 in2 , what dimensions should the
advertisement be to maximize the area of the printed region?
Answer
√ √
The optimal paper dimensions are 4 5 in by 6 5 in.
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 33 / 36
10
11. V63.0121, Calculus I Section 4.5 : Optimization Problems April 7, 2010
Solution
Notes
Let the dimensions of the
printed region be x and y , P 1.5 cm
the printed area, and A the Lorem ipsum dolor sit amet, con-
sectetur adipiscing elit. Nam
paper area. We wish to dapibus vehicula mollis. Proin nec
tristique mi. Pellentesque quis plac-
maximize P = xy subject to erat dolor. Praesent a nisl diam.
the constraint that Phasellus ut elit eu ligula accumsan
euismod. Nunc condimentum lacinia
risus a sodales. Morbi nunc risus,
tincidunt in tristique sit amet, ultri-
1 cm
1 cm
A = (x + 2)(y + 3) ≡ 120 y ces eu eros. Proin pellentesque ali-
quam nibh ut lobortis. Ut et sol-
licitudin ipsum. Proin gravida ligula
Isolating y in A ≡ 120 gives eget odio molestie rhoncus sed nec
massa. In ante lorem, imperdiet eget
120 tincidunt at, pharetra sit amet felis.
y= − 3 which yields Nunc nisi velit, tempus ac suscipit
x +2 quis, blandit vitae mauris. Vestibu-
lum ante ipsum primis in faucibus
orci luctus et ultrices posuere cubilia
120 120x Curae;
P=x −3 = −3x
x +2 x +2 1.5 cm
The domain of P is (0, ∞) x
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 34 / 36
Solution (Concluded)
We want to find the absolute maximum value of P. Taking derivatives, Notes
dP (x + 2)(120) − (120x)(1) 240 − 3(x + 2)2
= −3=
dx (x + 2)2 (x + 2)2
There is a single critical point when
√
(x + 2)2 = 80 =⇒ x = 4 5 − 2
(the negative critical point doesn’t count). The second derivative is
d 2P −480
=
dx 2 (x + 2)3
which is negative all along the domain of P. Hence the unique critical
√
point x = 4 5 − 2 cm is the absolute maximum of P. This means the
√ 120 √
paper width is 4 5 cm, and the paper length is √ = 6 5 cm.
4 5
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 35 / 36
Summary
Notes
Remember the checklist
Ask yourself: what is the objective?
Remember your geometry:
similar triangles
right triangles
trigonometric functions
V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 7, 2010 36 / 36
11