Partial Differentiation &
Application

           Week 9
Contents:
1.     Function with two variables
2.     First Partial Derivatives
3.     Applications of First Partial Derivatives
         Cob-Douglas Production Function
         Substitute and Complementary Commodities
1.     Second Partial Derivatives
2.     Application of Second Partial Derivatives
         Maxima and Minima of Functions of Several Variables*
         Lagrange Multipliers*
     *Additional topic
Functions of Two Variables
A Function of Two Variables

A real-valued function of two variables, f, consists of:
   1. A set A of ordered pairs of real numbers (x, y)
   called the domain of the function.

   2. A rule that associates with each ordered pair
   in the domain of f one and only one real number,
   denoted by z = f (x, y).
                                 Dependent
   Independent variables         variable


               Function of Two Variables
Example     Examples of problems with two variables.

   a. A company produces two products, A and B.
      The joint cost function (in RM) is given by:
           C = f ( x, y ) = 0.07 x 2 + 75 x + 85 y + 6000
   b. Country workshop manufactures both furnished
      and unfurnished furniture for home. The
      estimated quantities demanded each week of
      its desks in the finished and unfinished version
      are x and y units when the corresponding unit
      prices are p = 200 − 0.2x − 0.1y
                         q = 160 − 0.2x − 0.25y
          respectively.



                    Partial Derivatives: Application
Example
          Let f be the function defined by
                            2             3
            f ( x, y ) = 3 x y − 2 + y .
          Find f (0,3) and f (2, −1).

          f (0,3) = 3 ( 0 ) (3) − 2 + ( 3)
                           2                   3


                  = 25
          f (2, −1) = 3 ( 2 ) (−1) − 2 + ( −1)
                               2                   3


                   = −15



                   Function of Two Variables
Example
          Let f be the function defined by
                                x
              f ( x ,y ) =
                           x + y −3
          Find f ( 2,3 ),f ( 3,2 )

                          2
           f ( 2,3 ) =         =1
                       2+ 3− 3
                          3      3
           f ( 3,2 ) =         =
                       3+ 2− 3 2


                 Function of Two Variables
Example
            Find the domain of each function
          a. f ( x, y ) = 3 x − 2 y 2
            Since f (x, y) is defined for all real values
            of x and y (x and y is linear function), the
            domain of f is the set of all points (x, y)
            in the xy – plane.
                             x
          b. g( x, y ) =
                         2x + y − 3
          g(x, y) is defined as long as 2x + y – 3 is not 0.
          So the domain is the set of all points (x, y) in the
          xy – plane except those on the line y =–2x + 3.


                   Function of Two Variables
Question
           Let f be the function defined by

             f ( x, y ) =
                                (
                            100 1000 + 0.03 x y          2
                                                             )
                                                             0 .5


                                    ( 5 − 0. 2 y )   2

           Find the domain of the function
             g(x, y) is defined as long as   ( 5 − 0.2y )    2
                                                                 ≠0
                       ( 5 − 0.2y ) 2 ≠ 0
                       5 − 0.2 y ≠ 0
                       y ≠ 25
             So the domain is the set of all points (x, y) in
             the xy – plane except those on the line y=25



                    Function of Two Variables
Example Acrosonic manufactures a bookshelf loudspeaker
  system that may be bought fully assemble or in a kit. The
  demand equations that relate the unit prices, p and q to the
  quantities demanded weekly, x and y, of the assembled
  and kit versions of the loudspeaker systems are given by
                       1   1                     1   3
              p = 300 − x − y           q = 240 − x − y
                       4   8                     8   8
  What is the weekly total revenue function R (x,y)?
          R ( x, y ) = xp + yq
                            1   1            1   3 
                  = x  300 − x − y ÷+ y  240 − x − y ÷
                            4   8            8   8 
                      1 2 3 2 1
                  = − x − y − xy + 300 x + 240 y
                      4      8    4

                                                           10
                     Function of Two Variables
Recall the Graph of Two Variables


Ex. Plot (4, 2)

Ex. Plot (-2, 1)

Ex. Plot (2, -3)
                                               (4, 2)

                     (-2, 1)
                                        (2, -3)




                   Function of Two Variables
Graphs of Functions of Two Variables

   Three-dimensional coordinate system: (x, y, z)

          Ex. Plot (2, 5, 4)
                           z


                                4
                    2                       y
                           5

            x

                Function of Two Variables
Graphs of Functions of Two Variables


  Ex. Graph of f (x, y)= 4 – x2 – y2




            Function of Two Variables
First Partial Derivatives of f (x, y).

 f (x, y) is a function of two variables. The first
 partial derivative of f with respect to x at a
 point (x, y) is
  ∂f       f ( x + h, y ) − f ( x , y )
     = lim
  ∂x h→0               h
                                                  ∂
provided the limit exits. = f x = f x ( x , y ) = f ( x , y )
                                                 ∂x


                  Partial Derivatives
First Partial Derivatives of f (x, y).

f (x, y) is a function of two variables. The first
partial derivative of f with respect to y at a
point (x, y) is
    ∂f       f ( x, y + k ) − f ( x , y )
       = lim
    ∂y k →0              k
                                                         ∂
                                 = f y = f y ( x ,y ) =    f ( x ,y )
provided the limit exits.                               ∂y


                 Partial Derivatives
To get partial derivatives….
      To get        fx   assume y is a constant and
        differentiate with respect to x
Example            f ( x, y ) = xy 2 + x 2 y
               f x ( x, y ) = (1) y 2 + (2 x) y = y 2 + 2 xy
      To get        fy   assume x is a constant and
        differentiate with respect to y
Example               f ( x, y ) = xy 2 + x 2 y
               f y ( x, y ) = x(2 y ) + x 2 (1) = 2 xy + x 2


                          Partial Derivatives
Example   Compute the first partial derivatives
                f ( x, y ) = 3 x 2 y + x ln y
                                                         1
                  f x = 6 xy + ln y         f y = 3x + x  ÷
                                                    2

                                                          y


Example   Compute the first partial derivatives
                                        xy 2 + y
                       g ( x, y ) = e
                                                         2 xy 2 + y
              g y = ( 2 xy + 1) e    xy 2 + y
                                                   gx = y e



                         Partial Derivatives
Example   Compute the first partial derivatives
              f ( x, y ) = 3 x 2 y − 2 + y 3 .

             f x = 6 xy                     f y = 3x 2 + 3y 2


Example   Compute the first partial derivatives

              f ( x , y ) = 2x + 3y − 4
                    fx =2               fy =3



                          Partial Derivatives
The Cobb-Douglas Production Function
                                         1−b
                  f ( x, y ) = ax y  b


 • a and b are positive constants with 0 < b < 1.
 • x stands for the money spent on labor, y stands
   for the cost of capital equipment.
 • f measures the output of the finished product
   and is called the production function
   fx is the marginal productivity of labor.
   fy is the marginal productivity of capital.

                                                                       19
       Partial Derivatives: Application of First Partial Derivatives
Example   A certain production function is given by
              f ( x, y ) = 28 x y units, when x units of
                                     1/ 4   3/ 4

  labor and y units of capital are used. Find the
  marginal productivity of capital when labor = 81
  units and capital = 256 units.           1/ 4
                        1/ 4 −1/ 4     x
           f y = 21x y             = 21 ÷
                                        y
     When labor = 81 units and capital = 256 units,
                              1/ 4
          fy        81       3
               = 21     ÷ = 21 ÷ = 15.75
                    256      4
     So 15.75 units per unit increase in capital expenditure.


                                                                           20
           Partial Derivatives: Application of First Partial Derivatives
Question   A certain production function is given by
              f ( x, y ) = 28 x y units, when x units of
                                    1/ 4   3/ 4

   labor and y units of capital are used. Find the
   marginal productivity of labor when labor = 81 units
   and capital = 256 units.
                         1  −3 / 4 3 / 4
              f x = 28  x y = 7 x −3 / 4 y 3 / 4
                        4
      When labor = 81 units and capital = 256 units,

                  f x = 7(81) −3 / 4 (256) 3 / 4 = 49.78
     So 49.78 units per unit increase in labor expenditure.


                                                                            21
            Partial Derivatives: Application of First Partial Derivatives
Substitute and Complementary Commodities
 Suppose the demand equations that relate
 the quantities demanded, x and y, to the
 unit prices, p and q, of two commodities, A
 and B, are given by


         x = f(p,q) and             y = g(p,q)




                                                                     22
     Partial Derivatives: Application of First Partial Derivatives
Substitute and Complementary Commodities

Two commodities A and B are substitute commodities
if
              ∂f         ∂g
                 > 0 and    >0
              ∂q         ∂p
Two commodities A and B are complementary
commodities if
                ∂f         ∂g
                   < 0 and    <0
                ∂q         ∂p

                                                                     23
     Partial Derivatives: Application of First Partial Derivatives
Example   The demand function for two related commodities
          are
                    x = ae q-p
                    y = be p-q

          The marginal demand functions are
               δx = - ae q-p δy = be p-q
               δp              δp

                 δx = ae q-p           δy = - be p-q
                 δq                      δq

          Because δx/δq > 0 and δy/δp > 0, the two
          commodities are substitute commodities.


                                                                            24
            Partial Derivatives: Application of First Partial Derivatives
Question
   In a survey it was determined that the demand equation for VCRs
   is given by
           x = f ( p, q ) = 10, 000 − 10 p − e 0.5 q
   The demand equation for blank VCR tapes is given by

            y = g ( p, q ) = 50, 000 − 4000q − 10 p
   Where p and q denote the unit prices, respectively, and x and y
   denote the number of VCRs and the number of blank VCR tapes
   demanded each week. Determine whether these two products are
   substitute, complementary, or neither.




                                                                           25
           Partial Derivatives: Application of First Partial Derivatives
x = f ( p, q ) = 10, 000 − 10 p − e 0.5 q
       y = g ( p, q ) = 50, 000 − 4000q − 10 p

            ∂x                     ∂y
               = −10                  = −10
            ∂p                     ∂p
            ∂x                     ∂y
               = −0.5e 0.5 q          = −4000
            ∂q                     ∂q



Because δx/δq < 0 and δy/δp < 0, the two commodities are
complementary commodities.




      Partial Derivatives: Application of First Partial Derivatives
Second-Order Partial Derivatives

      ∂ f
      2
          ∂                            ∂2 f  ∂
f xx = 2 = ( f x )              f xy =      = ( fx )
      ∂x  ∂x                           ∂y∂x ∂y


      ∂ f
      2
          ∂                            ∂ f 2
                                            ∂
f yy = 2 = ( f y )              f yx =     = ( fy )
      ∂y  ∂y                           ∂x∂y ∂x




                                                              27
      Partial Derivatives: Second-Order Partial Derivatives
Example
          Find the second-order partial derivatives of the function
                    f ( x, y ) = 3 x 2 y + x ln y
                                                      1
                f x = 6 xy + ln y        f y = 3x + x  ÷
                                                    2

                                                       y
                                 x                         1                       1
f xx = 6 y              f yy   =− 2          f xy   = 6x +           f yx   = 6x +
                                 y                         y                       y
Example      Find the second-order partial derivatives of the function
                                                    2
                  a. f ( x, y ) = 3 x − 2 y

                   fx =3                       f y = −4 y
             f xx = 0            f yy = −4              f xy = 0   f yx = 0


                  Partial Derivatives: Second-Order Partial Derivatives
Example   Find the second-order partial derivatives of the function
                                                      xy 2
                              f ( x, y ) = e

     fx =
          ∂ xy 2
          ∂x
             e  ( )2 xy 2
                 =ye                                         fy =
                                                                  ∂ xy 2
                                                                  ∂y
                                                                     e     ( )
                                                                         = 2 xye xy 2




     f xx = y e 4 xy      2
                                                    f yx = 2 ye           xy 2
                                                                               ( 1 + xy )2



     f xy = 2 ye   xy 2       2
                                  (
                          + y 2 xye          xy 2
                                                    ) = 2 ye      xy 2
                                                                         (1 + xy )2


     f yy = 2 x e (   xy 2
                              +ye     (   xy 2
                                                             ))
                                                 • 2 xy = 2 xe             xy 2
                                                                                  (1 + 2 xy )2




                                                                                                 29
               Partial Derivatives: Second-Order Partial Derivatives
Maximum and Minimum of
  Functions of Several
       Variables


                         30
Relative Extrema of a Function of Two
Variables
Let f be a function defined on a region R containing
(a, b).
 f (a, b) is a relative maximum of f if f ( x, y ) ≤ f (a, b)
for all (x, y) sufficiently close to (a, b).
f (a, b) is a relative minimum of f if f ( x, y ) ≥ f (a, b)
for all (x, y) sufficiently close to (a, b).

*If the inequalities hold for all (x, y) in the domain of
f then the points are absolute extrema.

                                                                        31
       Partial Derivatives: Application of Second Partial Derivatives
Critical Point of f
A critical point of f is a point (a, b) in the
domain of f such that both
            ∂f                 ∂f
               ( a, b ) = 0 and ( a, b ) = 0
            ∂x                 ∂y

or at least one of the partial derivatives
does not exist.


                                                                      32
     Partial Derivatives: Application of Second Partial Derivatives
Determining Relative Extrema
1. Find all the critical points by solving the system
              f x = 0, f y = 0
2. The 2nd Derivative Test: Compute
             D( x, y ) = f xx f yy − f xy
                                        2



D ( a, b)   f xx (a, b)   Interpretation
  +           +           Relative min. at (a, b)
  +           –           Relative max. at (a, b)
  –                       Neither max. nor min. at (a, b)
                           saddle point
  0                       Test is inconclusive
                                                            33
Ex. Determine the relative extrema of the function
    f ( x, y ) = 2 x − x 2 − y 2
                                         So the only critical
 fx = 2 − 2x = 0     f y = −2 y = 0
                                         point is (1, 0).
      f xx = f yy = −2,   f xy = 0


D(1, 0) = ( −2 ) ( −2 ) − 0 2 = 4 > 0 and f xx ( 1, 0 ) = −2 < 0

        So f (1,0) = 1 is a relative maximum


                                                                   34
Application
 Ex: The total weekly revenue (in dollars) that Acrosonic realizes
 in producing and selling its bookshelf loudspeaker systems is
 given by               1 2 3 2 1
          R ( x, y ) = − x − y − xy + 300 x + 240 y
                        4   8   4
 where x denotes the number of fully assembled units and y
 denotes the number of kits produced and sold each week. The total
 weekly cost is given by
            C ( x, y ) = 180 x + 140 y + 5000
 Determine how many assembled units and how many kits
 Acrosonic should produce per week to maximize its profit.



                                                               35
P ( x, y ) = R ( x, y ) − C ( x , y )
             1 2 3 2 1
          = − x − y − xy + 120 x + 100 y − 5000
             4   8   4


      1   1
Px = − x − y + 120 = 0K ( 1)
      2   4
      3   1
Py = − y − x + 100 = 0K ( 2 )
      4   4



                                                  36
Substitute in K ( 1)
       y = −2 x + 480
   Substitute in K ( 2 )
           3                1
    Py = − ( −2 x + 480 ) − x + 100 = 0
           4                4
       = 6 x − 1440 − x + 400 = 0
                           ∴ x = 208
Substitute this value into the equation y = −2 x + 480
              ∴ y = 64
Therefore, P has the critical point (208,64)


                                                     37
1             1             3
   Pxx = −       Pxy = −       Pyy = −
           2             4             4
                                        2
                1  3   1     5
  D ( x, y ) =  − ÷ − ÷−  − ÷ =
                2  4   4  16

Since, D ( 208, 64 ) > 0 and Pxx ( 208, 64 ) < 0   , the
point (208,64) is a relative maximum of P.




                                                           38
Lagrange Multipliers

Reading: Mizrahi and Sullivan, 8th ed., 2004, Wiley
Chapter:17.5


                                                      39
Method of Lagrange Multipliers


A method to find the local minimum and maximum of a
function with two variables subject to conditions or
constraints on the variables involved.


Suppose that, subject to the constraint g(x,y)=0, the function
z=f(x,y) has a local maximum or a local minimum at the point
    .
                          ( x0 , y0 )

Form the function
                       F ( x, y , λ ) = f ( x, y ) + λ g ( x, y )

                                                                    40
Then there is a value of λ such that ( x0 , y0 , λ ) is a solution
of the system of equations
                    ∂F ∂f          ∂g
                       =     +λ       = 0 L ( 1)
                    ∂x ∂x          ∂x
                    ∂F ∂f          ∂g
                       =     +λ       = 0 L( 2)
                    ∂y ∂y          ∂y
                    ∂F
                       = g ( x, y ) = 0   L ( 3)
                    ∂λ


 provided all the partial derivatives exists.


                                                               41
Steps for Using the Method of Lagrange Multipliers

Step 1: Write the function to be maximized (or
        minimized) and the constraint in the form:
             Find the maximum (or minimum) value of
                        z = f ( x, y )


        subject to the constraint g ( x, y ) = 0

Step 2: Construct the function F:
              F ( x, y , λ ) = f ( x, y ) + λ g ( x, y )

                                                           42
Step 3: Set up the system of equations
                ∂F
                   = 0 L ( 1)
                ∂x
                ∂F
                   = 0 L( 2)
                ∂y
                ∂F
                   = g ( x, y ) = 0 L ( 3 )
                ∂λ
Step 4: Solve the system of equations for x, y and λ .

Step 5: Test the solution ( x0 , y0 , λ ) to determine
        maximum or minimum point.



                                                         43
Find D* = Fxx . Fyy - (Fxy)2

If   D* > 0 ⇒         Fxx < 0         ∴ maximum point
                      Fxx > 0         ∴ minimum point

     D* ≤ 0 ⇒            Test is inconclusive


Step 6: Evaluate z = f ( x, y ) at each solution ( x0 , y0 , λ )
       found in Step 5.



                                                                   44
Example:
Find the minimum of
       f(x,y) = 5x2 + 6y2 - xy
subject to the constraint
       x+2y = 24

Solution:
   F(x,y, λ) = 5x2 + 6y2 - xy + λ(x + 2y - 24)
   Fx =        δF = 10x - y + λ         ;      Fxx = 10
               δx
   Fy =        δF = 12y - x + 2λ        ;      Fyy = 12
               δy
   Fλ =        δF = x + 2y - 24         ;      Fxy = -1
               δλ

                                                          45
The critical point,
        10x - y + λ = 0
        12y - x + 2λ= 0
        x + 2y - 24= 0
The solution of the system is x = 6, y = 9, λ = -51

    D*=(10)(12)-(-1)2=119>0
    Fxx = 10>0

We find that f(x,y) has a local minimum at (6,9).

f(x,y) = 5(6)2+6(9)2-6(9)= 720



                                                      46
Example
 A manufacturer produces two types of engines, x units of type
 I and y units of type II. The joint profit function is given by
                 P ( x, y ) = x 2 + 3 xy − 6 y

 to maximize profit, how many engines of each type should be
 produced if there must be a total of 42 engines produced?




                                                               47
Maximize z = P ( x, y ) = x + 3xy − 6 y
                                       2


 Subject to constraint g ( x, y ) = x + y − 42 = 0
 F ( x, y , λ ) = P ( x , y ) + λ g ( x , y )
                = x 2 + 3xy − 6 y + λ ( x + y − 42 )
 ∂F
    = 2 x + 3 y + λ = 0 L ( 1) ;       Fxx = 2
 ∂x
 ∂F
    = 3x − 6 + λ = 0 L ( 2 ) ;             Fyy = 0
 ∂y
 ∂F
    = x + y − 42 = 0 L ( 3) ;           Fxy = 3
 ∂λ

The solution of the system is x = 33 y = 9 λ = −93.

                                                       48
Fxx = 2 > 0

      D* = (2)(0) − (3) 2 = −9 < 0


The test in inconclusive.




                                     49
Partial Differentiation & Application

Partial Differentiation & Application

  • 1.
  • 2.
    Contents: 1. Function with two variables 2. First Partial Derivatives 3. Applications of First Partial Derivatives  Cob-Douglas Production Function  Substitute and Complementary Commodities 1. Second Partial Derivatives 2. Application of Second Partial Derivatives  Maxima and Minima of Functions of Several Variables*  Lagrange Multipliers* *Additional topic
  • 3.
  • 4.
    A Function ofTwo Variables A real-valued function of two variables, f, consists of: 1. A set A of ordered pairs of real numbers (x, y) called the domain of the function. 2. A rule that associates with each ordered pair in the domain of f one and only one real number, denoted by z = f (x, y). Dependent Independent variables variable Function of Two Variables
  • 5.
    Example Examples of problems with two variables. a. A company produces two products, A and B. The joint cost function (in RM) is given by: C = f ( x, y ) = 0.07 x 2 + 75 x + 85 y + 6000 b. Country workshop manufactures both furnished and unfurnished furniture for home. The estimated quantities demanded each week of its desks in the finished and unfinished version are x and y units when the corresponding unit prices are p = 200 − 0.2x − 0.1y q = 160 − 0.2x − 0.25y respectively. Partial Derivatives: Application
  • 6.
    Example Let f be the function defined by 2 3 f ( x, y ) = 3 x y − 2 + y . Find f (0,3) and f (2, −1). f (0,3) = 3 ( 0 ) (3) − 2 + ( 3) 2 3 = 25 f (2, −1) = 3 ( 2 ) (−1) − 2 + ( −1) 2 3 = −15 Function of Two Variables
  • 7.
    Example Let f be the function defined by x f ( x ,y ) = x + y −3 Find f ( 2,3 ),f ( 3,2 ) 2 f ( 2,3 ) = =1 2+ 3− 3 3 3 f ( 3,2 ) = = 3+ 2− 3 2 Function of Two Variables
  • 8.
    Example Find the domain of each function a. f ( x, y ) = 3 x − 2 y 2 Since f (x, y) is defined for all real values of x and y (x and y is linear function), the domain of f is the set of all points (x, y) in the xy – plane. x b. g( x, y ) = 2x + y − 3 g(x, y) is defined as long as 2x + y – 3 is not 0. So the domain is the set of all points (x, y) in the xy – plane except those on the line y =–2x + 3. Function of Two Variables
  • 9.
    Question Let f be the function defined by f ( x, y ) = ( 100 1000 + 0.03 x y 2 ) 0 .5 ( 5 − 0. 2 y ) 2 Find the domain of the function g(x, y) is defined as long as ( 5 − 0.2y ) 2 ≠0 ( 5 − 0.2y ) 2 ≠ 0 5 − 0.2 y ≠ 0 y ≠ 25 So the domain is the set of all points (x, y) in the xy – plane except those on the line y=25 Function of Two Variables
  • 10.
    Example Acrosonic manufacturesa bookshelf loudspeaker system that may be bought fully assemble or in a kit. The demand equations that relate the unit prices, p and q to the quantities demanded weekly, x and y, of the assembled and kit versions of the loudspeaker systems are given by 1 1 1 3 p = 300 − x − y q = 240 − x − y 4 8 8 8 What is the weekly total revenue function R (x,y)? R ( x, y ) = xp + yq  1 1   1 3  = x  300 − x − y ÷+ y  240 − x − y ÷  4 8   8 8  1 2 3 2 1 = − x − y − xy + 300 x + 240 y 4 8 4 10 Function of Two Variables
  • 11.
    Recall the Graphof Two Variables Ex. Plot (4, 2) Ex. Plot (-2, 1) Ex. Plot (2, -3) (4, 2) (-2, 1) (2, -3) Function of Two Variables
  • 12.
    Graphs of Functionsof Two Variables Three-dimensional coordinate system: (x, y, z) Ex. Plot (2, 5, 4) z 4 2 y 5 x Function of Two Variables
  • 13.
    Graphs of Functionsof Two Variables Ex. Graph of f (x, y)= 4 – x2 – y2 Function of Two Variables
  • 14.
    First Partial Derivativesof f (x, y). f (x, y) is a function of two variables. The first partial derivative of f with respect to x at a point (x, y) is ∂f f ( x + h, y ) − f ( x , y ) = lim ∂x h→0 h ∂ provided the limit exits. = f x = f x ( x , y ) = f ( x , y ) ∂x Partial Derivatives
  • 15.
    First Partial Derivativesof f (x, y). f (x, y) is a function of two variables. The first partial derivative of f with respect to y at a point (x, y) is ∂f f ( x, y + k ) − f ( x , y ) = lim ∂y k →0 k ∂ = f y = f y ( x ,y ) = f ( x ,y ) provided the limit exits. ∂y Partial Derivatives
  • 16.
    To get partialderivatives….  To get fx assume y is a constant and differentiate with respect to x Example f ( x, y ) = xy 2 + x 2 y f x ( x, y ) = (1) y 2 + (2 x) y = y 2 + 2 xy  To get fy assume x is a constant and differentiate with respect to y Example f ( x, y ) = xy 2 + x 2 y f y ( x, y ) = x(2 y ) + x 2 (1) = 2 xy + x 2 Partial Derivatives
  • 17.
    Example Compute the first partial derivatives f ( x, y ) = 3 x 2 y + x ln y 1 f x = 6 xy + ln y f y = 3x + x  ÷ 2  y Example Compute the first partial derivatives xy 2 + y g ( x, y ) = e 2 xy 2 + y g y = ( 2 xy + 1) e xy 2 + y gx = y e Partial Derivatives
  • 18.
    Example Compute the first partial derivatives f ( x, y ) = 3 x 2 y − 2 + y 3 . f x = 6 xy f y = 3x 2 + 3y 2 Example Compute the first partial derivatives f ( x , y ) = 2x + 3y − 4 fx =2 fy =3 Partial Derivatives
  • 19.
    The Cobb-Douglas ProductionFunction 1−b f ( x, y ) = ax y b • a and b are positive constants with 0 < b < 1. • x stands for the money spent on labor, y stands for the cost of capital equipment. • f measures the output of the finished product and is called the production function fx is the marginal productivity of labor. fy is the marginal productivity of capital. 19 Partial Derivatives: Application of First Partial Derivatives
  • 20.
    Example A certain production function is given by f ( x, y ) = 28 x y units, when x units of 1/ 4 3/ 4 labor and y units of capital are used. Find the marginal productivity of capital when labor = 81 units and capital = 256 units. 1/ 4 1/ 4 −1/ 4 x f y = 21x y = 21 ÷  y When labor = 81 units and capital = 256 units, 1/ 4 fy  81  3 = 21 ÷ = 21 ÷ = 15.75  256  4 So 15.75 units per unit increase in capital expenditure. 20 Partial Derivatives: Application of First Partial Derivatives
  • 21.
    Question A certain production function is given by f ( x, y ) = 28 x y units, when x units of 1/ 4 3/ 4 labor and y units of capital are used. Find the marginal productivity of labor when labor = 81 units and capital = 256 units.  1  −3 / 4 3 / 4 f x = 28  x y = 7 x −3 / 4 y 3 / 4 4 When labor = 81 units and capital = 256 units, f x = 7(81) −3 / 4 (256) 3 / 4 = 49.78 So 49.78 units per unit increase in labor expenditure. 21 Partial Derivatives: Application of First Partial Derivatives
  • 22.
    Substitute and ComplementaryCommodities Suppose the demand equations that relate the quantities demanded, x and y, to the unit prices, p and q, of two commodities, A and B, are given by x = f(p,q) and y = g(p,q) 22 Partial Derivatives: Application of First Partial Derivatives
  • 23.
    Substitute and ComplementaryCommodities Two commodities A and B are substitute commodities if ∂f ∂g > 0 and >0 ∂q ∂p Two commodities A and B are complementary commodities if ∂f ∂g < 0 and <0 ∂q ∂p 23 Partial Derivatives: Application of First Partial Derivatives
  • 24.
    Example The demand function for two related commodities are x = ae q-p y = be p-q The marginal demand functions are δx = - ae q-p δy = be p-q δp δp δx = ae q-p δy = - be p-q δq δq Because δx/δq > 0 and δy/δp > 0, the two commodities are substitute commodities. 24 Partial Derivatives: Application of First Partial Derivatives
  • 25.
    Question In a survey it was determined that the demand equation for VCRs is given by x = f ( p, q ) = 10, 000 − 10 p − e 0.5 q The demand equation for blank VCR tapes is given by y = g ( p, q ) = 50, 000 − 4000q − 10 p Where p and q denote the unit prices, respectively, and x and y denote the number of VCRs and the number of blank VCR tapes demanded each week. Determine whether these two products are substitute, complementary, or neither. 25 Partial Derivatives: Application of First Partial Derivatives
  • 26.
    x = f( p, q ) = 10, 000 − 10 p − e 0.5 q y = g ( p, q ) = 50, 000 − 4000q − 10 p ∂x ∂y = −10 = −10 ∂p ∂p ∂x ∂y = −0.5e 0.5 q = −4000 ∂q ∂q Because δx/δq < 0 and δy/δp < 0, the two commodities are complementary commodities. Partial Derivatives: Application of First Partial Derivatives
  • 27.
    Second-Order Partial Derivatives ∂ f 2 ∂ ∂2 f ∂ f xx = 2 = ( f x ) f xy = = ( fx ) ∂x ∂x ∂y∂x ∂y ∂ f 2 ∂ ∂ f 2 ∂ f yy = 2 = ( f y ) f yx = = ( fy ) ∂y ∂y ∂x∂y ∂x 27 Partial Derivatives: Second-Order Partial Derivatives
  • 28.
    Example Find the second-order partial derivatives of the function f ( x, y ) = 3 x 2 y + x ln y 1 f x = 6 xy + ln y f y = 3x + x  ÷ 2  y x 1 1 f xx = 6 y f yy =− 2 f xy = 6x + f yx = 6x + y y y Example Find the second-order partial derivatives of the function 2 a. f ( x, y ) = 3 x − 2 y fx =3 f y = −4 y f xx = 0 f yy = −4 f xy = 0 f yx = 0 Partial Derivatives: Second-Order Partial Derivatives
  • 29.
    Example Find the second-order partial derivatives of the function xy 2 f ( x, y ) = e fx = ∂ xy 2 ∂x e ( )2 xy 2 =ye fy = ∂ xy 2 ∂y e ( ) = 2 xye xy 2 f xx = y e 4 xy 2 f yx = 2 ye xy 2 ( 1 + xy )2 f xy = 2 ye xy 2 2 ( + y 2 xye xy 2 ) = 2 ye xy 2 (1 + xy )2 f yy = 2 x e ( xy 2 +ye ( xy 2 )) • 2 xy = 2 xe xy 2 (1 + 2 xy )2 29 Partial Derivatives: Second-Order Partial Derivatives
  • 30.
    Maximum and Minimumof Functions of Several Variables 30
  • 31.
    Relative Extrema ofa Function of Two Variables Let f be a function defined on a region R containing (a, b). f (a, b) is a relative maximum of f if f ( x, y ) ≤ f (a, b) for all (x, y) sufficiently close to (a, b). f (a, b) is a relative minimum of f if f ( x, y ) ≥ f (a, b) for all (x, y) sufficiently close to (a, b). *If the inequalities hold for all (x, y) in the domain of f then the points are absolute extrema. 31 Partial Derivatives: Application of Second Partial Derivatives
  • 32.
    Critical Point off A critical point of f is a point (a, b) in the domain of f such that both ∂f ∂f ( a, b ) = 0 and ( a, b ) = 0 ∂x ∂y or at least one of the partial derivatives does not exist. 32 Partial Derivatives: Application of Second Partial Derivatives
  • 33.
    Determining Relative Extrema 1.Find all the critical points by solving the system f x = 0, f y = 0 2. The 2nd Derivative Test: Compute D( x, y ) = f xx f yy − f xy 2 D ( a, b) f xx (a, b) Interpretation + + Relative min. at (a, b) + – Relative max. at (a, b) – Neither max. nor min. at (a, b)  saddle point 0 Test is inconclusive 33
  • 34.
    Ex. Determine therelative extrema of the function f ( x, y ) = 2 x − x 2 − y 2 So the only critical fx = 2 − 2x = 0 f y = −2 y = 0 point is (1, 0). f xx = f yy = −2, f xy = 0 D(1, 0) = ( −2 ) ( −2 ) − 0 2 = 4 > 0 and f xx ( 1, 0 ) = −2 < 0 So f (1,0) = 1 is a relative maximum 34
  • 35.
    Application Ex: Thetotal weekly revenue (in dollars) that Acrosonic realizes in producing and selling its bookshelf loudspeaker systems is given by 1 2 3 2 1 R ( x, y ) = − x − y − xy + 300 x + 240 y 4 8 4 where x denotes the number of fully assembled units and y denotes the number of kits produced and sold each week. The total weekly cost is given by C ( x, y ) = 180 x + 140 y + 5000 Determine how many assembled units and how many kits Acrosonic should produce per week to maximize its profit. 35
  • 36.
    P ( x,y ) = R ( x, y ) − C ( x , y ) 1 2 3 2 1 = − x − y − xy + 120 x + 100 y − 5000 4 8 4 1 1 Px = − x − y + 120 = 0K ( 1) 2 4 3 1 Py = − y − x + 100 = 0K ( 2 ) 4 4 36
  • 37.
    Substitute in K( 1) y = −2 x + 480 Substitute in K ( 2 ) 3 1 Py = − ( −2 x + 480 ) − x + 100 = 0 4 4 = 6 x − 1440 − x + 400 = 0 ∴ x = 208 Substitute this value into the equation y = −2 x + 480 ∴ y = 64 Therefore, P has the critical point (208,64) 37
  • 38.
    1 1 3 Pxx = − Pxy = − Pyy = − 2 4 4 2  1  3   1  5 D ( x, y ) =  − ÷ − ÷−  − ÷ =  2  4   4  16 Since, D ( 208, 64 ) > 0 and Pxx ( 208, 64 ) < 0 , the point (208,64) is a relative maximum of P. 38
  • 39.
    Lagrange Multipliers Reading: Mizrahiand Sullivan, 8th ed., 2004, Wiley Chapter:17.5 39
  • 40.
    Method of LagrangeMultipliers A method to find the local minimum and maximum of a function with two variables subject to conditions or constraints on the variables involved. Suppose that, subject to the constraint g(x,y)=0, the function z=f(x,y) has a local maximum or a local minimum at the point . ( x0 , y0 ) Form the function F ( x, y , λ ) = f ( x, y ) + λ g ( x, y ) 40
  • 41.
    Then there isa value of λ such that ( x0 , y0 , λ ) is a solution of the system of equations ∂F ∂f ∂g = +λ = 0 L ( 1) ∂x ∂x ∂x ∂F ∂f ∂g = +λ = 0 L( 2) ∂y ∂y ∂y ∂F = g ( x, y ) = 0 L ( 3) ∂λ provided all the partial derivatives exists. 41
  • 42.
    Steps for Usingthe Method of Lagrange Multipliers Step 1: Write the function to be maximized (or minimized) and the constraint in the form: Find the maximum (or minimum) value of z = f ( x, y ) subject to the constraint g ( x, y ) = 0 Step 2: Construct the function F: F ( x, y , λ ) = f ( x, y ) + λ g ( x, y ) 42
  • 43.
    Step 3: Setup the system of equations ∂F = 0 L ( 1) ∂x ∂F = 0 L( 2) ∂y ∂F = g ( x, y ) = 0 L ( 3 ) ∂λ Step 4: Solve the system of equations for x, y and λ . Step 5: Test the solution ( x0 , y0 , λ ) to determine maximum or minimum point. 43
  • 44.
    Find D* =Fxx . Fyy - (Fxy)2 If D* > 0 ⇒ Fxx < 0 ∴ maximum point Fxx > 0 ∴ minimum point D* ≤ 0 ⇒ Test is inconclusive Step 6: Evaluate z = f ( x, y ) at each solution ( x0 , y0 , λ ) found in Step 5. 44
  • 45.
    Example: Find the minimumof f(x,y) = 5x2 + 6y2 - xy subject to the constraint x+2y = 24 Solution: F(x,y, λ) = 5x2 + 6y2 - xy + λ(x + 2y - 24) Fx = δF = 10x - y + λ ; Fxx = 10 δx Fy = δF = 12y - x + 2λ ; Fyy = 12 δy Fλ = δF = x + 2y - 24 ; Fxy = -1 δλ 45
  • 46.
    The critical point, 10x - y + λ = 0 12y - x + 2λ= 0 x + 2y - 24= 0 The solution of the system is x = 6, y = 9, λ = -51 D*=(10)(12)-(-1)2=119>0 Fxx = 10>0 We find that f(x,y) has a local minimum at (6,9). f(x,y) = 5(6)2+6(9)2-6(9)= 720 46
  • 47.
    Example A manufacturerproduces two types of engines, x units of type I and y units of type II. The joint profit function is given by P ( x, y ) = x 2 + 3 xy − 6 y to maximize profit, how many engines of each type should be produced if there must be a total of 42 engines produced? 47
  • 48.
    Maximize z =P ( x, y ) = x + 3xy − 6 y 2 Subject to constraint g ( x, y ) = x + y − 42 = 0 F ( x, y , λ ) = P ( x , y ) + λ g ( x , y ) = x 2 + 3xy − 6 y + λ ( x + y − 42 ) ∂F = 2 x + 3 y + λ = 0 L ( 1) ; Fxx = 2 ∂x ∂F = 3x − 6 + λ = 0 L ( 2 ) ; Fyy = 0 ∂y ∂F = x + y − 42 = 0 L ( 3) ; Fxy = 3 ∂λ The solution of the system is x = 33 y = 9 λ = −93. 48
  • 49.
    Fxx = 2> 0 D* = (2)(0) − (3) 2 = −9 < 0 The test in inconclusive. 49

Editor's Notes

  • #20 Fx measures the rate of change of production with respect to the amount of money expended for labor, with the level of capital expenditure held constant. Fy measures the rate of change of production with respect to the amount expended on capital, with the level of labor expenditure held constant/fixed.
  • #41 Maximize f(x,y) subject to g(x,y) = 0