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Section 4.5
              Optimization Problems

                  V63.0121.006/016, Calculus I

                         New York University


                          April 6, 2010


Announcements

   Thank you for the evaluations
   Quiz 4 April 16 on §§4.1–4.4
                                               .   .   .   .   .   .
Announcements




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




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




     “Very knowledgeable”




                                                                   .   .   .    .       .      .

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




     “Very knowledgeable”
     “Knows how to teach”




                                                                   .   .   .    .       .      .

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




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




                                                                   .   .   .    .       .      .

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




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




                                                                   .   .   .    .       .      .

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




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




                                                                   .   .   .    .       .      .

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




     “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 6, 2010       3 / 36
Evaluations: The bad



     Too fast, not enough examples




                                                                   .   .   .    .       .      .

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



     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




                                                                   .   .   .    .       .      .

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



     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




                                                                   .   .   .    .       .      .

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



     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 6, 2010       4 / 36
Evaluations: The ugly




     “The projector blows.”




                                                                   .   .   .    .       .      .

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




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




                                                                   .   .   .    .       .      .

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




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




                                                                   .   .   .    .       .      .

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




     “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 6, 2010       5 / 36
A slide on slides

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




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

     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”




                                                                   .   .   .    .       .      .

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

     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




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




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

     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

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


Example
What is the rectangle of fixed perimeter with maximum area?




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


Example
What is the rectangle of fixed perimeter with maximum area?

Solution

    Draw a rectangle.




                          .




                                             .   .   .   .    .   .
Leading by Example


Example
What is the rectangle of fixed perimeter with maximum area?

Solution

    Draw a rectangle.




                          .
                                  .
                                  ℓ



                                             .   .   .   .    .   .
Leading by Example


Example
What is the rectangle of fixed perimeter with maximum area?

Solution

     Draw a rectangle.


                                                                   w
                                                                   .

                                 .
                                               .
                                               ℓ



                                                                   .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.




                                                                   .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.
     This is a function of two variables, not one. But the perimeter is
     fixed.




                                                                   .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.
     This is a function of two variables, not one. But the perimeter is
     fixed.
                                        p − 2w
     Since p = 2ℓ + 2w, we have ℓ =            ,
                                           2




                                                                   .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.
     This is a function of two variables, not one. But the perimeter is
     fixed.
                                        p − 2w
     Since p = 2ℓ + 2w, we have ℓ =            , so
                                           2
                               p − 2w      1             1
                  A = ℓw =            · w = (p − 2w)(w) = pw − w2
                                  2        2             2




                                                                     .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.
     This is a function of two variables, not one. But the perimeter is
     fixed.
                                        p − 2w
     Since p = 2ℓ + 2w, we have ℓ =            , so
                                           2
                               p − 2w      1             1
                  A = ℓw =            · w = (p − 2w)(w) = pw − w2
                                  2        2             2


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




                                                                     .   .   .     .       .     .

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

     Let its length be ℓ and its width be w. The objective function is
     area A = ℓw.
     This is a function of two variables, not one. But the perimeter is
     fixed.
                                        p − 2w
     Since p = 2ℓ + 2w, we have ℓ =            , so
                                           2
                               p − 2w      1             1
                  A = ℓw =            · w = (p − 2w)(w) = pw − w2
                                  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 6, 2010   11 / 36
Solution Concluded

                                                                       1
We use the Closed Interval Method for A(w) =                             pw − w2 on [0, p/2].
                                                                       2
     At the endpoints, A(0) = A(p/2) = 0.




                                                                   .      .    .     .       .     .

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

                                                                       1
We use the Closed Interval Method for A(w) =                             pw − w2 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




                                                                   .      .    .     .       .     .

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

                                                                       1
We use the Closed Interval Method for A(w) =                             pw − w2 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




                                                                   .      .    .     .       .     .

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

                                                                       1
We use the Closed Interval Method for A(w) =                             pw − w2 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 ℓ = as well.
               4


                                                                   .      .    .     .       .     .

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

                                                                       1
We use the Closed Interval Method for A(w) =                             pw − w2 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 ℓ = as well.
               4
     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
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
Strategies for Problem Solving




 1. Understand the problem
 2. Devise a plan
 3. Carry out the plan
 4. Review and extend




                                                              György Pólya
                                                          (Hungarian, 1887–1985)
                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   14 / 36
The Text in the Box



 1. Understand the Problem. What is known? What is unknown?
    What are the conditions?




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   15 / 36
The Text in the Box



 1. Understand the Problem. What is known? What is unknown?
    What are the conditions?
 2. Draw a diagram.




                                                                   .   .   .     .       .     .

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




                                                                   .   .   .     .       .     .

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




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   15 / 36
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 the
    given information to eliminate all but one of them.




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   15 / 36
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 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
Name    [_
                             Problem Solving Strategy
                             Draw 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 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 6, 2010   16 / 36
Recall: The Closed Interval Method
See Section 4.1




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 6, 2010   17 / 36
Recall: The First Derivative Test
See 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).
      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 6, 2010   18 / 36
Recall: The Second Derivative Test
See 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) 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).



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   V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   19 / 36
Which to use when?

           CIM                       1DT                               2DT
 Pro       – no need for             – works on                        – works on
           inequalities              non-closed,                       non-closed,
           – gets global             non-bounded                       non-bounded
           extrema                   intervals                         intervals
           automatically             – only one derivative             – no need for
                                                                       inequalities
 Con       – only for closed         – Uses inequalities               – More derivatives
           bounded intervals         – More work at                    – less conclusive
                                     boundary than CIM                 than 1DT
                                                                       – more work at
                                                                       boundary than CIM




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   20 / 36
Which to use when?

           CIM                       1DT                               2DT
 Pro       – no need for             – works on                        – works on
           inequalities              non-closed,                       non-closed,
           – gets global             non-bounded                       non-bounded
           extrema                   intervals                         intervals
           automatically             – only one derivative             – no need for
                                                                       inequalities
 Con       – only for closed         – Uses inequalities               – More derivatives
           bounded intervals         – More work at                    – less conclusive
                                     boundary than CIM                 than 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 6, 2010   20 / 36
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
Another Example


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?




                                                                   .   .   .     .       .     .

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

 1. Everybody understand?




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


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?




                                                                   .   .   .     .       .     .

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


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




                                                                   .   .   .     .       .     .

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


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 6, 2010   24 / 36
Solution

 1. Everybody understand?




                                                                   .   .   .     .       .     .

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

 1. Everybody understand?
 2. Draw a diagram.




                                                                   .   .   .     .       .     .

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

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?




                               .     .

                                                   .
                 .


                                                                       .   .   .     .       .     .

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

 1. Everybody understand?
 2. Draw a diagram.




                                                                   .   .   .     .       .     .

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

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




                                                                   .   .   .     .       .     .

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

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?




                               .     .

                                                   .
                 .


                                                                       .   .   .     .       .     .

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

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?
                                                      .
                                                      ℓ


                               w
                               .

                                   .     .

                                                       .
                 .


                                                                           .   .   .     .       .     .

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

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




                                                                   .   .   .     .       .     .

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




                                                                   .   .   .     .       .     .

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




                                                                      .   .   .     .       .     .

  V63.0121, Calculus I (NYU)      Section 4.5 Optimization Problems               April 6, 2010   29 / 36
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]
    dQ                                 p
 6.    = p − 4w, which is zero when w = .
    dw                                 4




                                                                      .   .   .     .       .     .

  V63.0121, Calculus I (NYU)      Section 4.5 Optimization Problems               April 6, 2010   29 / 36
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]
    dQ                                 p
 6.    = p − 4w, which is zero when w = .
    dw                                 4




                                                                      .   .   .     .       .     .

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

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?




                                                                   .   .   .     .       .     .

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

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 ℓ and w. The amount of
fence needed is f = 2ℓ + 3w. Since ℓw = 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 6, 2010   30 / 36
Diagram


                                   .                           .




                         w
                         .



                               .
                                                         .
                                                         ℓ

                              f = 2ℓ + 3w                    A = ℓw ≡ 216


                                                                           .   .   .     .       .     .

 V63.0121, Calculus I (NYU)            Section 4.5 Optimization Problems               April 6, 2010   31 / 36
Solution (Continued)
                                                                   2A
We need to find the minimum value of f(w) =                           + 3w on (0, ∞).
                                                                   w




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   32 / 36
Solution (Continued)
                                                                   2A
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




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   32 / 36
Solution (Continued)
                                                                   2A
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
     Since f′′ (w) = 4Aw−3 , which is positive for all positive w, the
     critical point is a minimum, in fact the global minimum.




                                                                   .   .   .     .       .     .

  V63.0121, Calculus I (NYU)   Section 4.5 Optimization Problems               April 6, 2010   32 / 36
Solution (Continued)
                                                                   2A
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
     Since f′′ (w) = 4Aw−3 , 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
     ℓ= =              = 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 6, 2010   32 / 36
Try this one



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?




                                                                   .   .   .     .       .     .

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



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 6, 2010   33 / 36
Solution
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,
                                                                   consectetur adipiscing elit. Nam
paper area. We wish to                                             dapibus vehicula mollis. Proin nec
                                                                   tristique mi.      Pellentesque quis
maximize P = xy subject to                                         placerat 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,
 A = (x + 2)(y + 3) ≡ 120




                                                        . cm




                                                                                                             . cm
                                                 y
                                                 .                 ultrices eu eros. Proin pellentesque
                                                                   aliquam nibh ut lobortis.         Ut et




                                                        1




                                                                                                             1
                                                                   sollicitudin ipsum.      Proin gravida
Isolating y in A ≡ 120 gives                                       ligula eget odio molestie rhoncus
                                                                   sed nec massa. In ante lorem,
     120                                                           imperdiet eget tincidunt at, pharetra
y=         − 3 which yields                                        sit amet felis.      Nunc nisi velit,
     x+2                                                           tempus ac suscipit quis, blandit
                                                                   vitae mauris. Vestibulum ante ipsum
       (          )                                                primis in faucibus orci luctus et
         120           120x                                    .   ultrices posuere cubilia 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 6, 2010        34 / 36
Solution (Concluded)
We want to find the absolute maximum value of P. Taking derivatives,

           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

                                       d2 P    −480
                                          2
                                            =
                                       dx     (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
                    √                              120      √
the 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 6, 2010   35 / 36
Summary




    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 6, 2010   36 / 36

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  • 1. Section 4.5 Optimization Problems V63.0121.006/016, Calculus I New York University April 6, 2010 Announcements Thank you for the evaluations Quiz 4 April 16 on §§4.1–4.4 . . . . . .
  • 2. Announcements 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 6, 2010 2 / 36
  • 3. Evaluations: The good “Very knowledgeable” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36
  • 4. Evaluations: The good “Very knowledgeable” “Knows how to teach” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36
  • 5. Evaluations: The good “Very knowledgeable” “Knows how to teach” “Very good at projecting voice” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36
  • 6. Evaluations: The good “Very knowledgeable” “Knows how to teach” “Very good at projecting voice” “Office hours are accessible” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36
  • 7. Evaluations: The good “Very knowledgeable” “Knows how to teach” “Very good at projecting voice” “Office hours are accessible” “Clean” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 3 / 36
  • 8. Evaluations: The good “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 6, 2010 3 / 36
  • 9. Evaluations: The bad Too fast, not enough examples . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36
  • 10. Evaluations: The bad 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36
  • 11. Evaluations: The bad 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 4 / 36
  • 12. Evaluations: The bad 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 6, 2010 4 / 36
  • 13. Evaluations: The ugly “The projector blows.” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 5 / 36
  • 14. Evaluations: The ugly “The projector blows.” “Sometimes condescending/rude.” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 5 / 36
  • 15. Evaluations: The ugly “The projector blows.” “Sometimes condescending/rude.” “Can’t pick his nose without checking his notes, and he still gets it wrong the first time.” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 5 / 36
  • 16. Evaluations: The ugly “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 6, 2010 5 / 36
  • 17. A slide on slides Pro “Excellent slides and examples” “clear and well-rehearsed” “Slides are easy to follow and posted” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36
  • 18. A slide on slides 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” . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36
  • 19. A slide on slides 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 6 / 36
  • 20. My handwriting . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 7 / 36
  • 21. A slide on slides 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 6, 2010 8 / 36
  • 22. 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
  • 23. Leading by Example Example What is the rectangle of fixed perimeter with maximum area? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36
  • 24. Leading by Example Example What is the rectangle of fixed perimeter with maximum area? Solution Draw a rectangle. . . . . . . .
  • 25. Leading by Example Example What is the rectangle of fixed perimeter with maximum area? Solution Draw a rectangle. . . ℓ . . . . . .
  • 26. Leading by Example Example What is the rectangle of fixed perimeter with maximum area? Solution Draw a rectangle. w . . . ℓ . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 10 / 36
  • 27. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36
  • 28. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. This is a function of two variables, not one. But the perimeter is fixed. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36
  • 29. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. This is a function of two variables, not one. But the perimeter is fixed. p − 2w Since p = 2ℓ + 2w, we have ℓ = , 2 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36
  • 30. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. This is a function of two variables, not one. But the perimeter is fixed. p − 2w Since p = 2ℓ + 2w, we have ℓ = , so 2 p − 2w 1 1 A = ℓw = · w = (p − 2w)(w) = pw − w2 2 2 2 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36
  • 31. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. This is a function of two variables, not one. But the perimeter is fixed. p − 2w Since p = 2ℓ + 2w, we have ℓ = , so 2 p − 2w 1 1 A = ℓw = · w = (p − 2w)(w) = pw − w2 2 2 2 Now we have A as a function of w alone (p is constant). . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 11 / 36
  • 32. Solution Continued Let its length be ℓ and its width be w. The objective function is area A = ℓw. This is a function of two variables, not one. But the perimeter is fixed. p − 2w Since p = 2ℓ + 2w, we have ℓ = , so 2 p − 2w 1 1 A = ℓw = · w = (p − 2w)(w) = pw − w2 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 6, 2010 11 / 36
  • 33. Solution Concluded 1 We use the Closed Interval Method for A(w) = pw − w2 on [0, p/2]. 2 At the endpoints, A(0) = A(p/2) = 0. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36
  • 34. Solution Concluded 1 We use the Closed Interval Method for A(w) = pw − w2 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36
  • 35. Solution Concluded 1 We use the Closed Interval Method for A(w) = pw − w2 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36
  • 36. Solution Concluded 1 We use the Closed Interval Method for A(w) = pw − w2 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 ℓ = as well. 4 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 12 / 36
  • 37. Solution Concluded 1 We use the Closed Interval Method for A(w) = pw − w2 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 ℓ = as well. 4 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
  • 38. 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
  • 39. Strategies for Problem Solving 1. Understand the problem 2. Devise a plan 3. Carry out the plan 4. Review and extend György Pólya (Hungarian, 1887–1985) . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 14 / 36
  • 40. The Text in the Box 1. Understand the Problem. What is known? What is unknown? What are the conditions? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36
  • 41. The Text in the Box 1. Understand the Problem. What is known? What is unknown? What are the conditions? 2. Draw a diagram. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36
  • 42. 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. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36
  • 43. 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36
  • 44. 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 the given information to eliminate all but one of them. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 15 / 36
  • 45. 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 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
  • 46. Name [_ Problem Solving Strategy Draw 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 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 6, 2010 16 / 36
  • 47. Recall: The Closed Interval Method See Section 4.1 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 6, 2010 17 / 36
  • 48. Recall: The First Derivative Test See 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). 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 6, 2010 18 / 36
  • 49. Recall: The Second Derivative Test See 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) 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 6, 2010 19 / 36
  • 50. Which to use when? CIM 1DT 2DT Pro – no need for – works on – works on inequalities non-closed, non-closed, – gets global non-bounded non-bounded extrema intervals intervals automatically – only one derivative – no need for inequalities Con – only for closed – Uses inequalities – More derivatives bounded intervals – More work at – less conclusive boundary than CIM than 1DT – more work at boundary than CIM . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 20 / 36
  • 51. Which to use when? CIM 1DT 2DT Pro – no need for – works on – works on inequalities non-closed, non-closed, – gets global non-bounded non-bounded extrema intervals intervals automatically – only one derivative – no need for inequalities Con – only for closed – Uses inequalities – More derivatives bounded intervals – More work at – less conclusive boundary than CIM than 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 6, 2010 20 / 36
  • 52. 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
  • 53. Another Example 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? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 22 / 36
  • 54. Solution 1. Everybody understand? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 23 / 36
  • 55. Another Example 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? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 24 / 36
  • 56. Another Example 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 24 / 36
  • 57. Another Example 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 6, 2010 24 / 36
  • 58. Solution 1. Everybody understand? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 25 / 36
  • 59. Solution 1. Everybody understand? 2. Draw a diagram. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 25 / 36
  • 60. Diagram 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? . . . . . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 26 / 36
  • 61. Solution 1. Everybody understand? 2. Draw a diagram. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 27 / 36
  • 62. Solution 1. Everybody understand? 2. Draw a diagram. 3. Length and width are ℓ and w. Length of wire used is p. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 27 / 36
  • 63. Diagram 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? . . . . . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 28 / 36
  • 64. Diagram 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? . ℓ w . . . . . . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 28 / 36
  • 65. Solution 1. Everybody understand? 2. Draw a diagram. 3. Length and width are ℓ and w. Length of wire used is p. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36
  • 66. 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. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36
  • 67. 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] . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36
  • 68. 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] dQ p 6. = p − 4w, which is zero when w = . dw 4 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36
  • 69. 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] dQ p 6. = p − 4w, which is zero when w = . dw 4 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 29 / 36
  • 70. 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] 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 6, 2010 29 / 36
  • 71. Your turn 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? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 30 / 36
  • 72. Your turn 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 ℓ and w. The amount of fence needed is f = 2ℓ + 3w. Since ℓw = 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 6, 2010 30 / 36
  • 73. Diagram . . w . . . ℓ f = 2ℓ + 3w A = ℓw ≡ 216 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 31 / 36
  • 74. Solution (Continued) 2A We need to find the minimum value of f(w) = + 3w on (0, ∞). w . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36
  • 75. Solution (Continued) 2A 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 . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36
  • 76. Solution (Continued) 2A 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 Since f′′ (w) = 4Aw−3 , which is positive for all positive w, the critical point is a minimum, in fact the global minimum. . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 32 / 36
  • 77. Solution (Continued) 2A 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 Since f′′ (w) = 4Aw−3 , 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 ℓ= = = 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 6, 2010 32 / 36
  • 78. Try this one 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? . . . . . . V63.0121, Calculus I (NYU) Section 4.5 Optimization Problems April 6, 2010 33 / 36
  • 79. Try this one 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 6, 2010 33 / 36
  • 80. Solution 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, consectetur adipiscing elit. Nam paper area. We wish to dapibus vehicula mollis. Proin nec tristique mi. Pellentesque quis maximize P = xy subject to placerat 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, A = (x + 2)(y + 3) ≡ 120 . cm . cm y . ultrices eu eros. Proin pellentesque aliquam nibh ut lobortis. Ut et 1 1 sollicitudin ipsum. Proin gravida Isolating y in A ≡ 120 gives ligula eget odio molestie rhoncus sed nec massa. In ante lorem, 120 imperdiet eget tincidunt at, pharetra y= − 3 which yields sit amet felis. Nunc nisi velit, x+2 tempus ac suscipit quis, blandit vitae mauris. Vestibulum ante ipsum ( ) primis in faucibus orci luctus et 120 120x . ultrices posuere cubilia 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 6, 2010 34 / 36
  • 81. Solution (Concluded) We want to find the absolute maximum value of P. Taking derivatives, 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 d2 P −480 2 = dx (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 √ 120 √ the 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 6, 2010 35 / 36
  • 82. Summary 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 6, 2010 36 / 36