82
. . . . . . Section 4.5 Optimization Problems V63.0121.006/016, Calculus I New York University April 6, 2010 Announcements I Thank you for the evaluations I Quiz 4 April 16 on §§4.1–4.4

Lesson 20: Optimization (slides)

Embed Size (px)

DESCRIPTION

Optimization problems are just max/min problems with some additional reading comprehension.

Citation preview

Page 1: Lesson 20: Optimization (slides)

. . . . . .

Section 4.5Optimization Problems

V63.0121.006/016, Calculus I

New York University

April 6, 2010

Announcements

I Thank you for the evaluationsI Quiz 4 April 16 on §§4.1–4.4

Page 2: Lesson 20: Optimization (slides)

. . . . . .

Announcements

I Thank you for the evaluationsI Quiz 4 April 16 on §§4.1–4.4

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 2 / 36

Page 3: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”

I “Knows how to teach”I “Very good at projecting voice”I “Office hours are accessible”I “Clean”I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 4: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”I “Knows how to teach”

I “Very good at projecting voice”I “Office hours are accessible”I “Clean”I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 5: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”I “Knows how to teach”I “Very good at projecting voice”

I “Office hours are accessible”I “Clean”I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 6: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”I “Knows how to teach”I “Very good at projecting voice”I “Office hours are accessible”

I “Clean”I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 7: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”I “Knows how to teach”I “Very good at projecting voice”I “Office hours are accessible”I “Clean”

I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 8: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The good

I “Very knowledgeable”I “Knows how to teach”I “Very good at projecting voice”I “Office hours are accessible”I “Clean”I “Great syllabus”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36

Page 9: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The bad

I Too fast, not enough examples

I Not enough time to do everythingI Lecture is not the only learning time (recitation and independent

study)I I try to balance concept and procedure

I Too many proofsI In this course we care about conceptsI There will be conceptual problems on the examI Concepts are the keys to overcoming templated problems

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36

Page 10: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The bad

I Too fast, not enough examplesI Not enough time to do everythingI Lecture is not the only learning time (recitation and independent

study)I I try to balance concept and procedure

I Too many proofsI In this course we care about conceptsI There will be conceptual problems on the examI Concepts are the keys to overcoming templated problems

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36

Page 11: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The bad

I Too fast, not enough examplesI Not enough time to do everythingI Lecture is not the only learning time (recitation and independent

study)I I try to balance concept and procedure

I Too many proofs

I In this course we care about conceptsI There will be conceptual problems on the examI Concepts are the keys to overcoming templated problems

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36

Page 12: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The bad

I Too fast, not enough examplesI Not enough time to do everythingI Lecture is not the only learning time (recitation and independent

study)I I try to balance concept and procedure

I Too many proofsI In this course we care about conceptsI There will be conceptual problems on the examI Concepts are the keys to overcoming templated problems

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36

Page 13: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The ugly

I “The projector blows.”

I “Sometimes condescending/rude.”I “Can’t pick his nose without checking his notes, and he still gets it

wrong the first time.”I “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 6, 2010 5 / 36

Page 14: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The ugly

I “The projector blows.”I “Sometimes condescending/rude.”

I “Can’t pick his nose without checking his notes, and he still gets itwrong the first time.”

I “If I were chained to a desk and forced to see this guy teach, Iwould chew my arm off in order to get free.”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 5 / 36

Page 15: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The ugly

I “The projector blows.”I “Sometimes condescending/rude.”I “Can’t pick his nose without checking his notes, and he still gets it

wrong the first time.”

I “If I were chained to a desk and forced to see this guy teach, Iwould chew my arm off in order to get free.”

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 5 / 36

Page 16: Lesson 20: Optimization (slides)

. . . . . .

Evaluations: The ugly

I “The projector blows.”I “Sometimes condescending/rude.”I “Can’t pick his nose without checking his notes, and he still gets it

wrong the first time.”I “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 6, 2010 5 / 36

Page 17: Lesson 20: Optimization (slides)

. . . . . .

A slide on slides

I ProI “Excellent slides and examples”I “clear and well-rehearsed”I “Slides are easy to follow and posted”

I ConI “I wish he would actually use the chalkboard occasionally”I “Sometimes the slides skip steps”I “too fast”

I Why I like themI Board handwriting not an issueI Easy to put online; notetaking is more than transcription

I What we can doI if you have suggestions for details to put in, I’m listeningI Feel free to ask me to fill in something on the board

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36

Page 18: Lesson 20: Optimization (slides)

. . . . . .

A slide on slides

I ProI “Excellent slides and examples”I “clear and well-rehearsed”I “Slides are easy to follow and posted”

I ConI “I wish he would actually use the chalkboard occasionally”I “Sometimes the slides skip steps”I “too fast”

I Why I like themI Board handwriting not an issueI Easy to put online; notetaking is more than transcription

I What we can doI if you have suggestions for details to put in, I’m listeningI Feel free to ask me to fill in something on the board

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36

Page 19: Lesson 20: Optimization (slides)

. . . . . .

A slide on slides

I ProI “Excellent slides and examples”I “clear and well-rehearsed”I “Slides are easy to follow and posted”

I ConI “I wish he would actually use the chalkboard occasionally”I “Sometimes the slides skip steps”I “too fast”

I Why I like themI Board handwriting not an issueI Easy to put online; notetaking is more than transcription

I What we can doI if you have suggestions for details to put in, I’m listeningI Feel free to ask me to fill in something on the board

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36

Page 20: Lesson 20: Optimization (slides)

. . . . . .

My handwriting

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 7 / 36

Page 21: Lesson 20: Optimization (slides)

. . . . . .

A slide on slides

I ProI “Excellent slides and examples”I “clear and well-rehearsed”I “Slides are easy to follow and posted”

I ConI “I wish he would actually use the chalkboard occasionally”I “Sometimes the slides skip steps”I “too fast”

I Why I like themI Board handwriting not an issueI Easy to put online; notetaking is more than transcription

I What we can doI if you have suggestions for details to put in, I’m listeningI Feel free to ask me to fill in something on the board

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 8 / 36

Page 22: Lesson 20: Optimization (slides)

. . . . . .

Outline

Leading by Example

The Text in the Box

More Examples

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 9 / 36

Page 23: Lesson 20: Optimization (slides)

. . . . . .

Leading by Example

Example

What is the rectangle of fixed perimeter with maximum area?

Solution

I Draw a rectangle.

..ℓ

.w

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36

Page 24: Lesson 20: Optimization (slides)

. . . . . .

Leading by Example

Example

What is the rectangle of fixed perimeter with maximum area?

Solution

I Draw a rectangle.

.

.ℓ

.w

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36

Page 25: Lesson 20: Optimization (slides)

. . . . . .

Leading by Example

Example

What is the rectangle of fixed perimeter with maximum area?

Solution

I Draw a rectangle.

..ℓ

.w

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36

Page 26: Lesson 20: Optimization (slides)

. . . . . .

Leading by Example

Example

What is the rectangle of fixed perimeter with maximum area?

Solution

I Draw a rectangle.

..ℓ

.w

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36

Page 27: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2, so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).I 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 6, 2010 11 / 36

Page 28: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2, so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).I 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 6, 2010 11 / 36

Page 29: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2,

so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).I 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 6, 2010 11 / 36

Page 30: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2, so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).I 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 6, 2010 11 / 36

Page 31: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2, so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).

I The natural domain of this function is [0,p/2] (we want to makesure A(w) ≥ 0).

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36

Page 32: Lesson 20: Optimization (slides)

. . . . . .

Solution Continued

I Let its length be ℓ and its width be w. The objective function isarea A = ℓw.

I This is a function of two variables, not one. But the perimeter isfixed.

I Since p = 2ℓ+ 2w, we have ℓ =p− 2w

2, so

A = ℓw =p− 2w

2· w =

12(p− 2w)(w) =

12pw− w2

I Now we have A as a function of w alone (p is constant).I 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 6, 2010 11 / 36

Page 33: Lesson 20: Optimization (slides)

. . . . . .

Solution Concluded

We use the Closed Interval Method for A(w) =12pw− w2 on [0,p/2].

I At the endpoints, A(0) = A(p/2) = 0.

I To find the critical points, we finddAdw

=12p− 2w.

I The critical points are when

0 =12p− 2w =⇒ w =

p4

I Since this is the only critical point, it must be the maximum. In thiscase ℓ =

p4as well.

I We have a square! The maximal area is A(p/4) = p2/16.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36

Page 34: Lesson 20: Optimization (slides)

. . . . . .

Solution Concluded

We use the Closed Interval Method for A(w) =12pw− w2 on [0,p/2].

I At the endpoints, A(0) = A(p/2) = 0.

I To find the critical points, we finddAdw

=12p− 2w.

I The critical points are when

0 =12p− 2w =⇒ w =

p4

I Since this is the only critical point, it must be the maximum. In thiscase ℓ =

p4as well.

I We have a square! The maximal area is A(p/4) = p2/16.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36

Page 35: Lesson 20: Optimization (slides)

. . . . . .

Solution Concluded

We use the Closed Interval Method for A(w) =12pw− w2 on [0,p/2].

I At the endpoints, A(0) = A(p/2) = 0.

I To find the critical points, we finddAdw

=12p− 2w.

I The critical points are when

0 =12p− 2w =⇒ w =

p4

I Since this is the only critical point, it must be the maximum. In thiscase ℓ =

p4as well.

I We have a square! The maximal area is A(p/4) = p2/16.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36

Page 36: Lesson 20: Optimization (slides)

. . . . . .

Solution Concluded

We use the Closed Interval Method for A(w) =12pw− w2 on [0,p/2].

I At the endpoints, A(0) = A(p/2) = 0.

I To find the critical points, we finddAdw

=12p− 2w.

I The critical points are when

0 =12p− 2w =⇒ w =

p4

I Since this is the only critical point, it must be the maximum. In thiscase ℓ =

p4as well.

I We have a square! The maximal area is A(p/4) = p2/16.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36

Page 37: Lesson 20: Optimization (slides)

. . . . . .

Solution Concluded

We use the Closed Interval Method for A(w) =12pw− w2 on [0,p/2].

I At the endpoints, A(0) = A(p/2) = 0.

I To find the critical points, we finddAdw

=12p− 2w.

I The critical points are when

0 =12p− 2w =⇒ w =

p4

I Since this is the only critical point, it must be the maximum. In thiscase ℓ =

p4as well.

I We have a square! The maximal area is A(p/4) = p2/16.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36

Page 38: Lesson 20: Optimization (slides)

. . . . . .

Outline

Leading by Example

The Text in the Box

More Examples

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 13 / 36

Page 39: Lesson 20: Optimization (slides)

. . . . . .

Strategies for Problem Solving

1. Understand the problem2. Devise a plan3. Carry out the plan4. Review and extend

György Pólya(Hungarian, 1887–1985)

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 14 / 36

Page 40: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 symbols5. 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 6, 2010 15 / 36

Page 41: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 symbols5. 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 6, 2010 15 / 36

Page 42: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 symbols5. 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 6, 2010 15 / 36

Page 43: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 thegiven information to eliminate all but one of them.

6. Find the absolute maximum (or minimum, depending on theproblem) of the function on its domain.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36

Page 44: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 symbols5. 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 theproblem) of the function on its domain.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36

Page 45: Lesson 20: Optimization (slides)

. . . . . .

The Text in the Box

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 symbols5. 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 6, 2010 15 / 36

Page 46: Lesson 20: Optimization (slides)

. . . . . .

Name [_

Problem Solving StrategyDraw a Picture

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 pictureto solve the problem.

crayons

What number do Iadd to 5 to get 8?

8 - = 55 + 3 = 8

CHECK

Does your answer make sense?Explain.

Draw a picture to solve the problem.Write how many were given away.I. I had 10 pencils.

I gave some away.I have 3 left. How manypencils did I give away?

~7

What numberdo I add to 3to make 10?

13iftill:ii ?11

ftI'•'«II

ft A

H 11M i l

U U U U> U U

I I

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 16 / 36

Page 47: Lesson 20: Optimization (slides)

. . . . . .

Recall: The Closed Interval MethodSee Section 4.1

To find the extreme values of a function f on [a,b], we need to:I Evaluate f at the endpoints a and bI Evaluate f at the critical points x where either f′(x) = 0 or f is not

differentiable at x.I The points with the largest function value are the global maximum

pointsI 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 6, 2010 17 / 36

Page 48: Lesson 20: Optimization (slides)

. . . . . .

Recall: The First Derivative TestSee Section 4.3

Theorem (The First Derivative Test)

Let f be continuous on [a,b] and c a critical point of f in (a,b).I If f′ changes from negative to positive at c, then c is a local

minimum.I If f′ changes from positive to negative at c, then c is a local

maximum.I 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 6, 2010 18 / 36

Page 49: Lesson 20: Optimization (slides)

. . . . . .

Recall: The Second Derivative TestSee Section 4.3

Theorem (The Second Derivative Test)

Let f, f′, and f′′ be continuous on [a,b]. Let c be be a point in (a,b) withf′(c) = 0.

I If f′′(c) < 0, then f(c) is a local maximum.I If f′′(c) > 0, then f(c) is a local minimum.

Warning

If f′′(c) = 0, the second derivative test is inconclusive (this does notmean c is neither; we just don’t know yet).

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 19 / 36

Page 50: Lesson 20: Optimization (slides)

. . . . . .

Which to use when?

CIM 1DT 2DTPro – no need for

inequalities– gets globalextremaautomatically

– works onnon-closed,non-boundedintervals– only one derivative

– works onnon-closed,non-boundedintervals– no need forinequalities

Con – only for closedbounded intervals

– Uses inequalities– More work atboundary than CIM

– More derivatives– less conclusivethan 1DT– more work atboundary than CIM

I Use CIM if it applies: the domain is a closed, bounded intervalI 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 6, 2010 20 / 36

Page 51: Lesson 20: Optimization (slides)

. . . . . .

Which to use when?

CIM 1DT 2DTPro – no need for

inequalities– gets globalextremaautomatically

– works onnon-closed,non-boundedintervals– only one derivative

– works onnon-closed,non-boundedintervals– no need forinequalities

Con – only for closedbounded intervals

– Uses inequalities– More work atboundary than CIM

– More derivatives– less conclusivethan 1DT– more work atboundary than CIM

I Use CIM if it applies: the domain is a closed, bounded intervalI 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 6, 2010 20 / 36

Page 52: Lesson 20: Optimization (slides)

. . . . . .

Outline

Leading by Example

The Text in the Box

More Examples

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 21 / 36

Page 53: Lesson 20: Optimization (slides)

. . . . . .

Another Example

Example (The Best Fencing Plan)

A rectangular plot of farmland will be bounded on one side by a riverand on the other three sides by a single-strand electric fence. With800m of wire at your disposal, what is the largest area you canenclose, and what are its dimensions?

I Known: amount of fence usedI Unknown: area enclosedI Objective: maximize areaI Constraint: fixed fence length

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 22 / 36

Page 54: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?

2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 23 / 36

Page 55: Lesson 20: Optimization (slides)

. . . . . .

Another Example

Example (The Best Fencing Plan)

A rectangular plot of farmland will be bounded on one side by a riverand on the other three sides by a single-strand electric fence. With800m of wire at your disposal, what is the largest area you canenclose, and what are its dimensions?

I Known: amount of fence usedI Unknown: area enclosedI Objective: maximize areaI Constraint: fixed fence length

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 24 / 36

Page 56: Lesson 20: Optimization (slides)

. . . . . .

Another Example

Example (The Best Fencing Plan)

A rectangular plot of farmland will be bounded on one side by a riverand on the other three sides by a single-strand electric fence. With800m of wire at your disposal, what is the largest area you canenclose, and what are its dimensions?

I Known: amount of fence usedI Unknown: area enclosed

I Objective: maximize areaI Constraint: fixed fence length

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 24 / 36

Page 57: Lesson 20: Optimization (slides)

. . . . . .

Another Example

Example (The Best Fencing Plan)

A rectangular plot of farmland will be bounded on one side by a riverand on the other three sides by a single-strand electric fence. With800m of wire at your disposal, what is the largest area you canenclose, and what are its dimensions?

I Known: amount of fence usedI Unknown: area enclosedI Objective: maximize areaI Constraint: fixed fence length

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 24 / 36

Page 58: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?

2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 25 / 36

Page 59: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.

3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 25 / 36

Page 60: Lesson 20: Optimization (slides)

. . . . . .

Diagram

A rectangular plot of farmland will be bounded on one side by a riverand 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?

.

.

.

.

.w

.ℓ

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 26 / 36

Page 61: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.

3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 27 / 36

Page 62: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.

4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 27 / 36

Page 63: Lesson 20: Optimization (slides)

. . . . . .

Diagram

A rectangular plot of farmland will be bounded on one side by a riverand 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?

.

.

.

.

.w

.ℓ

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 28 / 36

Page 64: Lesson 20: Optimization (slides)

. . . . . .

Diagram

A rectangular plot of farmland will be bounded on one side by a riverand 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?

.

.

.

.

.w

.ℓ

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 28 / 36

Page 65: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.

4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 66: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.

5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 67: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 68: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 69: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4.

Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 70: Lesson 20: Optimization (slides)

. . . . . .

Solution

1. Everybody understand?2. Draw a diagram.3. Length and width are ℓ and w. Length of wire used is p.4. Q = area = ℓw.5. Since p = ℓ+ 2w, we have ℓ = p− 2w and so

Q(w) = (p− 2w)(w) = pw− 2w2

The domain of Q is [0,p/2]

6. dQdw

= p− 4w, which is zero when w =p4. Q(0) = Q(p/2) = 0, but

Q(p4

)= p · p

4− 2 · p

2

16=

p2

8= 80,000m2

so the critical point is the absolute maximum.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36

Page 71: Lesson 20: Optimization (slides)

. . . . . .

Your turn

Example (The shortest fence)

A 216m2 rectangular pea patch is to be enclosed by a fence anddivided into two equal parts by another fence parallel to one of itssides. What dimensions for the outer rectangle will require the smallesttotal length of fence? How much fence will be needed?

SolutionLet the length and width of the pea patch be ℓ and w. The amount offence needed is f = 2ℓ+ 3w. Since ℓw = A, a constant, we have

f(w) = 2Aw

+ 3w.

The domain is all positive numbers.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 30 / 36

Page 72: Lesson 20: Optimization (slides)

. . . . . .

Your turn

Example (The shortest fence)

A 216m2 rectangular pea patch is to be enclosed by a fence anddivided into two equal parts by another fence parallel to one of itssides. What dimensions for the outer rectangle will require the smallesttotal length of fence? How much fence will be needed?

SolutionLet the length and width of the pea patch be ℓ and w. The amount offence needed is f = 2ℓ+ 3w. Since ℓw = A, a constant, we have

f(w) = 2Aw

+ 3w.

The domain is all positive numbers.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 30 / 36

Page 73: Lesson 20: Optimization (slides)

. . . . . .

Diagram

.

. .

.ℓ

.w

f = 2ℓ+ 3w A = ℓw ≡ 216

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 31 / 36

Page 74: Lesson 20: Optimization (slides)

. . . . . .

Solution (Continued)

We need to find the minimum value of f(w) =2Aw

+ 3w on (0,∞).

I We havedfdw

= −2Aw2 + 3

which is zero when w =

√2A3.

I Since f′′(w) = 4Aw−3, which is positive for all positive w, thecritical point is a minimum, in fact the global minimum.

I So the area is minimized when w =

√2A3

= 12 and

ℓ =Aw

=

√3A2

= 18. The amount of fence needed is

f

(√2A3

)= 2 ·

√3A2

+ 3√

2A3

= 2√6A = 2

√6 · 216 = 72m

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36

Page 75: Lesson 20: Optimization (slides)

. . . . . .

Solution (Continued)

We need to find the minimum value of f(w) =2Aw

+ 3w on (0,∞).I We have

dfdw

= −2Aw2 + 3

which is zero when w =

√2A3.

I Since f′′(w) = 4Aw−3, which is positive for all positive w, thecritical point is a minimum, in fact the global minimum.

I So the area is minimized when w =

√2A3

= 12 and

ℓ =Aw

=

√3A2

= 18. The amount of fence needed is

f

(√2A3

)= 2 ·

√3A2

+ 3√

2A3

= 2√6A = 2

√6 · 216 = 72m

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36

Page 76: Lesson 20: Optimization (slides)

. . . . . .

Solution (Continued)

We need to find the minimum value of f(w) =2Aw

+ 3w on (0,∞).I We have

dfdw

= −2Aw2 + 3

which is zero when w =

√2A3.

I Since f′′(w) = 4Aw−3, which is positive for all positive w, thecritical point is a minimum, in fact the global minimum.

I So the area is minimized when w =

√2A3

= 12 and

ℓ =Aw

=

√3A2

= 18. The amount of fence needed is

f

(√2A3

)= 2 ·

√3A2

+ 3√

2A3

= 2√6A = 2

√6 · 216 = 72m

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36

Page 77: Lesson 20: Optimization (slides)

. . . . . .

Solution (Continued)

We need to find the minimum value of f(w) =2Aw

+ 3w on (0,∞).I We have

dfdw

= −2Aw2 + 3

which is zero when w =

√2A3.

I Since f′′(w) = 4Aw−3, which is positive for all positive w, thecritical point is a minimum, in fact the global minimum.

I So the area is minimized when w =

√2A3

= 12 and

ℓ =Aw

=

√3A2

= 18. The amount of fence needed is

f

(√2A3

)= 2 ·

√3A2

+ 3√

2A3

= 2√6A = 2

√6 · 216 = 72m

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36

Page 78: Lesson 20: Optimization (slides)

. . . . . .

Try this one

Example

An advertisement consists of a rectangular printed region plus 1 inmargins on the sides and 1.5 in margins on the top and bottom. If thetotal area of the advertisement is to be 120 in2, what dimensions shouldthe advertisement be to maximize the area of the printed region?

AnswerThe optimal paper dimensions are 4

√5 in by 6

√5 in.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 33 / 36

Page 79: Lesson 20: Optimization (slides)

. . . . . .

Try this one

Example

An advertisement consists of a rectangular printed region plus 1 inmargins on the sides and 1.5 in margins on the top and bottom. If thetotal area of the advertisement is to be 120 in2, what dimensions shouldthe advertisement be to maximize the area of the printed region?

AnswerThe optimal paper dimensions are 4

√5 in by 6

√5 in.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 33 / 36

Page 80: Lesson 20: Optimization (slides)

. . . . . .

Solution

Let the dimensions of theprinted region be x and y, Pthe printed area, and A thepaper area. We wish tomaximize P = xy subject tothe constraint that

A = (x+ 2)(y+ 3) ≡ 120

Isolating y in A ≡ 120 gives

y =120x+ 2

− 3 which yields

P = x(

120x+ 2

− 3)

=120xx+ 2

−3x

The domain of P is (0,∞)

.

.Lorem ipsum dolor sit amet,consectetur adipiscing elit. Namdapibus vehicula mollis. Proin nectristique mi. Pellentesque quisplacerat dolor. Praesent a nisl diam.Phasellus ut elit eu ligula accumsaneuismod. Nunc condimentumlacinia risus a sodales. Morbi nuncrisus, tincidunt in tristique sit amet,ultrices eu eros. Proin pellentesquealiquam nibh ut lobortis. Ut etsollicitudin ipsum. Proin gravidaligula eget odio molestie rhoncussed nec massa. In ante lorem,imperdiet eget tincidunt at, pharetrasit amet felis. Nunc nisi velit,tempus ac suscipit quis, blanditvitae mauris. Vestibulum ante ipsumprimis in faucibus orci luctus etultrices posuere cubilia Curae;

.1.5 cm

.1.5 cm

.1cm

.1cm

.x

.y

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 34 / 36

Page 81: Lesson 20: Optimization (slides)

. . . . . .

Solution (Concluded)

We want to find the absolute maximum value of P. Taking derivatives,

dPdx

=(x+ 2)(120)− (120x)(1)

(x+ 2)2− 3 =

240− 3(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

d2Pdx2

=−480

(x+ 2)3

which is negative all along the domain of P. Hence the unique criticalpoint x =

(4√5− 2

)cm is the absolute maximum of P. This means

the paper width is 4√5 cm, and the paper length is

1204√5= 6

√5 cm.

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 35 / 36

Page 82: Lesson 20: Optimization (slides)

. . . . . .

Summary

I Remember the checklistI Ask yourself: what is the objective?I Remember your geometry:

I similar trianglesI right trianglesI trigonometric functions

V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 36 / 36