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Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.
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Page 1: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Applied Max and Min Problems

Objective: To use the methods of this chapter to solve applied

optimization problems.

Page 2: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Classification

• The applied optimization problems that we will consider in this section fall into the following two categories:

1) Problems that reduce to maximizing or minimizing a continuous function over a finite closed interval.

2) Problems that reduce to maximizing or minimizing a continuous function over an infinite interval or a finite interval that is not closed.

Page 3: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

• A garden is to be laid out in a rectangular area and protected by a chicken wire fence. What is the largest possible area of the garden if only 100 running feet of chicken wire is available?

Page 4: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

• A garden is to be laid out in a rectangular area and protected by a chicken wire fence. What is the largest possible area of the garden if only 100 running feet of chicken wire is available?

• x = length of the rectangle (ft)• y = width of the rectangle (ft)• A = area of the rectangle (ft2)• The domain is 0 < x < 50

Page 5: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

• x = length of the rectangle (ft)• y = width of the rectangle (ft)• A = area of the rectangle (ft2) P = perimeter of fence• We are maximizing the area, so we need an equation

for the area in one variable. We will use two separate equations and substitute to get an area equation in one variable.

Page 6: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

• x = length of the rectangle (ft)• y = width of the rectangle (ft)• A = area of the rectangle (ft2) P = perimeter of fence• We are maximizing the area, so we need an equation

for the area in one variable. We will use two separate equations and substitute to get an area equation in one variable.

A = xy P = 2x + 2y; 100 = 2x + 2y; y = 50 - x

Page 7: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

• x = length of the rectangle (ft)• y = width of the rectangle (ft)• A = area of the rectangle (ft2) P = perimeter of fence• A = xy P = 2x + 2y; 100 = 2x + 2y; y = 50 – x A = x(50 – x) = 50x – x2

dA/dx = 50 – 2x ___+___|___-___ 25 max

Page 8: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

___+___|___-___ 25 max• We must now check the endpoints as well as the

critical numbers.• f(0) = 0• f(25) = 625• f(50) = 0

Page 9: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 1

___+___|___-___ 25 max• We must now check the endpoints as well as the

critical numbers.• f(0) = 0• f(25) = 625 Maximum area of 625 ft2 @ x = 25 ft• f(50) = 0

Page 10: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 2

• An open box is to be made from a 16-inch by 30-inch piece of cardboard by cutting out squares of equal size from the four corners and bending up the sides. What size should the squares be to obtain a box with the largest volume?

• The largest the squares can be is 8 in (why?) so the domain is 0 < x < 8

Page 11: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 2

• An open box is to be made from a 16-inch by 30-inch piece of cardboard by cutting out squares of equal size from the four corners and bending up the sides. What size should the squares be to obtain a box with the largest volume?

• We are maximizing the volume, so we need an equation for volume. V = x(30 – 2x)(16 – 2x)

Page 12: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 2

• We are maximizing the volume, so we need an equation for volume. V = x(30 – 2x)(16 – 2x)

• V = 480x – 92x2 + 4x3

• dV/dx = 480 – 184x + 12x2

= 4(x – 12)(3x – 10)

Page 13: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 2

• We are maximizing the volume, so we need an equation for volume. V = x(30 – 2x)(16 – 2x)

• V = 480x – 92x2 + 4x3

• dV/dx = 480 – 184x + 12x2

= 4(x – 12)(3x – 10)• The only critical number in the domain is 10/3 so:• f(0) = 0• f(10/3) = 726• f(8) = 0

Page 14: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 2

• We are maximizing the volume, so we need an equation for volume. V = x(30 – 2x)(16 – 2x)

• V = 480x – 92x2 + 4x3

• dV/dx = 480 – 184x + 12x2

= 4(x – 12)(3x – 10)• The only critical number in the domain is 10/3 so:• f(0) = 0• f(10/3) = 726 Max volume of 726 in3 @ x = 10/3 in• f(8) = 0

Page 15: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 3

• An offshore oil well is located at a point W that is 5km from the closest point A on a straight shoreline. Oil is to be piped from W to a shore point B that is 8km from A by piping it on a straight line under water from W to some shore point P between A & B and then onto B via pipe along the shoreline. If the cost of laying pipe is $1,000,000/km under water and $500,000/km over land, where should the point P be located to minimize the cost of laying the pipe?

Page 16: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 3

• x = the distance (in km) between A and P• c = cost (in millions) for the entire pipeline• Using the Pythagorean Theorem, the distance from

W to P is • The distance from P to B is (8 – x)• We are minimizing cost, so we need a cost equation.

252 x

)8(2

1251 2 xxc

Page 17: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 3

• Now, we take the derivative to find the critical numbers.

)8(2

1251 2 xxc

2

1

252

x

x

dx

dc

2

1

250

2

x

x

Page 18: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 3

• Now, we take the derivative to find the critical numbers.

)8(2

1251 2 xxc

2

1

252

x

x

dx

dc

2

1

252

x

x

252 2 xx

254 22 xx

3

252 x3

5x2

1

250

2

x

x

Page 19: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 3

• We now need to check the endpoints and the critical number to find the min.

• The domain is 0 < x < 8 so:• F(0) = 9• F(8) = 9.433

• Min cost of 8.33 million @ x = km 33.83

5

f 3

5

Page 20: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 4

• Find the radius and height of the right circular cylinder of largest volume that can be inscribed in a right circular cone with radius 6 in and height 10 in.

Page 21: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 4

• Find the radius and height of the right circular cylinder of largest volume that can be inscribed in a right circular cone with radius 6 in and height 10 in.

• r = radius of cylinder• h = height of cylinder• V = volume

hrV 2

Page 22: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 4

• Again, we need to eliminate one of the variables. We will do this with similar triangles.

hrV 2

6

1010

r

h

rh3

510

322

3

510

3

510 rrrrV

Page 23: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 4

• Now, we take the derivative and find the critical points.

32

3

510 rrV 2520 rr

dr

dV

)4(5 rrdr

dV

Page 24: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 4

• The domain of the radius is 0 < r < 6, so we check the endpoints and the critical number.

• f(0) = 0• f(4) = 167.55 Max volume of 167.55 in3 @ x = 4 in• f(6) = 0

)4(5 rrdr

dV

Page 25: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• A closed cylindrical can is to hold 1000 cm3 of liquid. How should we choose the height and radius to minimize the amount of material needed to manufacture the can?

• There are no physical restraints on this problem, so this is not a finite interval. We need to confirm that our critical number is a minimum.

Page 26: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• A closed cylindrical can is to hold 1000 cm3 of liquid. How should we choose the height and radius to minimize the amount of material needed to manufacture the can?

• h = height (cm) of can• r = radius (cm) of can• S = surface area (cm2) of can

Page 27: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• Again, we will find two equations and substitute to get the surface area equation in one variable.

• h = height (cm) of can• r = radius (cm) of can• S = surface area (cm2) of can

rhrS 22 2

hr 21000

2

1000

rh

Page 28: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• Again, we will find two equations and substitute to get the surface area equation in one variable.

• h = height (cm) of can• r = radius (cm) of can• S = surface area (cm2) of can

rhrS 22 2

hr 21000

2

1000

rh

22 100022

rrrS

rrS

20002 2

Page 29: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• Now we find the derivative and check the critical number.

rrS

20002 2

2

20004

rr

dr

dS

2

200040

rr

Page 30: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• Now we find the derivative and check the critical number.

rrS

20002 2

2

20004

rr

dr

dS

420003 r

cmr 4.52

200040

rr

2

20004

rr

20004 3 r

Page 31: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 5

• Now we find the derivative and check the critical number.

____-___|___+___ 5.4 min

rrS

20002 2 2

20004

rr

dr

dS

420003 r cmr 4.5

Page 32: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• Find a point on the curve y = x2 that is closest to the point (18, 0).

Page 33: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• Find a point on the curve y = x2 that is closest to the point (18, 0).

• The distance L from (18, 0) and an arbitrary point

(x, y) on the curve is:• Since y = x2, we can say that

22 )0()18( yxL

42)18( xxL

Page 34: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• Find a point on the curve y = x2 that is closest to the point (18, 0).

• The distance L from (18, 0) and an arbitrary point

(x, y) on the curve is:• Since y = x2, we can say that

• We are told that the distance L and the square of the distance L2 are minimized at the same value.

22 )0()18( yxL

42)18( xxL

Page 35: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• We will now take the derivative of L2 to find any critical points

42)18( xxL

3624 3 xxdx

dS

32436242 xxxLS

Page 36: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• We will now take the derivative of L2 to find any critical points

• This will factor to (x – 2)(2x2 + 4x + 9) [trust me!] ___-___|___+___ 2 min

42)18( xxL

3624 3 xxdx

dS

32436242 xxxLS

Page 37: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Example 6

• We will now take the derivative of L2 to find any critical points

• This will factor to (x – 2)(2x2 + 4x + 9) [trust me!] ___-___|___+___ The closest point is (2, 4) 2 min

42)18( xxL

3624 3 xxdx

dS

32436242 xxxLS

Page 38: Applied Max and Min Problems Objective: To use the methods of this chapter to solve applied optimization problems.

Homework

• Section 4.5

• 1, 3, 5, 11,19, 21, 23


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