Lecture 9- Decision Making(1)

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    Decision Making

    Dr Anisur Rahman

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    Decision Making

    Decision makingis the cognitive process leadingto the selection of a course of action amongvariations.

    Every decision making process produces a finalchoice.

    Decision making is a reasoning process whichcan be rational or irrational, can be based on

    explicit assumptions.

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    Decision Making Tools

    Allocation or Assignment umanresource planning!

    E"uipment planning!

    #roductivity comparison!

    $nvestment!

    Repair replacement %trategy

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    uman Resources #lanning

    Purpose: &o maintain an ade"uate and uniform supplyofsuitable experienced labour.

    &o reduce overmanningduring downturns indemand

    &o avoid sharp fluctuationin each trade.

    Factors Influencing Demand & Supply of Labour

    'ages ( Rewards )$ncentive

    %kills

    *ther factors such as +eographical location, working conditions,%ocial

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    Allocation/Assignment Method

    Assumptions:

    1. No. of People (rows) = No. Tass (columns)

    !. The num"ers within the matri# are the costs

    associated with each particular tas.

    $i# alternati%es are a%aila"le &' = &(!)(1) = .

    Say you have three rushed tasks (T1), (T2) &(T3) and you have ADAMS, BROWN andCOOPER are available to perform tasks atdierent speed/ost)!

    T1 T T!

    "D"MS -- - /

    #$%' 0 -1 --

    (%%P)$ 2 -3 4

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    T1T1 T2T2 T3T3ADAMSADAMS #11 #1$ #%

    BROWNBROWN # #1' #11

    COOPERCOOPER # #12 #

    T1T1 T2T2 T3T3

    ADAMSADAMS #* # #'

    BROWNBROWN #' #2 #3

    COOPERCOOPER #2 #* #'

    %tep -5 Row operation select the lowest cost element in each row andsubtract this element from all elements in that row to develop a new matrix

    %tep 35 6olumn operation select the lowest cost element in each row inthe new matrix and subtract this element from all elements in that row todevelop a new matrix

    T1T1 T2T2 T3T3

    ADAMSADAMS #* #% #'

    BROWNBROWN #' #' #3

    COOPERCOOPER #2 #3 #'

    6heck each row andcolumn has at leastone 718! if not go step 3

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    %tep 95 %trike off all the columns and rows that contain at least one :ero

    with minimum number of hori:ontal and vertical lines T1T1 T2T2 T3T3

    ADAMSADAMS #* #% #'

    BROWNBROWN #' #' #3

    COOPERCOOPER #2 #3 #'

    %tep 5 6heck5 ; of lines < ; of =obs, if not means optimisation has not yetarrived. $n that case select the minimum uncovered element and subtractthis min element from all the uncovered elements to get a new matrixAnd strike off all the rows and columns again with minimum numbers ofhori:ontal and vertical lines

    T1T1 T2T2 T3T3ADAMSADAMS #3 #$ #'

    BROWNBROWN #' #' #3

    COOPERCOOPER #' #1 #'

    %tep 5 6heck ;>ines < ;=obs, if yes optimal solution arrived

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    T1T1

    T2T2

    T3T3

    ADAMSADAMS #3 #$ #'

    BROWNBROWN #' #' #3

    COOPERCOOPER #' #1 #'

    %tep ?5 %elect the row@column with minumum ; of :ero, assign the row #erson tothe column obs corresponding to the :ero and strike off that column and row

    %tep ?5 Do the same things for remaining rows and columns and assign the

    corresponding #ersons to obs

    T1T1 T2T2 T3T3

    ADAMSADAMS

    BROWNBROWN #' #'

    COOPERCOOPER #' #1

    Assign ob&9 to Adam

    Assign ob&- to 6ooper

    T1T1 T2T2 T3T3

    ADAMSADAMS

    BROWNBROWN #'

    COOPERCOOPER

    Assign ob&3 to Brown

    &otal cost < /C-1C2 < 3?

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    &he assignment is made as follows5-. %elect the row or column with fewest number of

    :eroes in it

    3. %elect an element in that row@column that is :ero

    9. Assign the person in that row to that =ob in thecolumn

    . Delete assigned row and column

    ?. Repeat the preceding procedure.

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    ou can ha%e an optimal solution "* Maximising efficiency

    Example:

    The onl* difference is that *ou need to con%ert the matri# firstinto a minimising opportunit* costta"le and then proceed with

    the pre%ious four steps as "efore.

    &- &3 &9 &

    ADA% 31 /1 ?1 ??

    BR*' /1 91 01 4?

    6**#ER 01 -11 21 01

    DAF$% /? 01 4? 41

    Efficiency

    &- &3 &9 &

    ADA% 01 1 ?1 ?BR*' 1 41 31 3?

    6**#ER 31 1 -1 31

    DAF$% 9? 31 3? 91

    *pportunity 6ost

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    T1 T! T& T+

    A,AM$ +- - 1- 5

    0N !- 2- - 2

    300P4 !- - 1- !-

    ,A56$15 - 2 1-

    T1 T! T& T+

    A,AM$ !2 - 1- -0N 2 2- - -

    300P4 2 - 1- 12

    ,A56$ 0 - 2 2

    + $traight lines co%ering all 7eros in the matri# 0ptimal $olution:

    3ooper will definitel* perform Tas T! (1--8)

    ,a%is will perform Tas T1 (28)

    rown Tas & (9-8) finall* Adams will perform Tas + (228)

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    atrix Reduction Guestion

    our compan* has one surplus truc in each of the towns A; ; 3;

    ,; and 4 and one deficit truc in each of the construction sites 1; !;

    &; +; 2 and . The distance "etween the towns and the construction

    sites in ilometres is shown in the matri# "elow (see Ta"le 1).

    Assign the trucs from towns to construction sites to minimise the

    total distance co%ered.

    Site 1 Site Site ! Site * Site + Site ,

    " -3 -1 -? 33 -0 0

    # -1 -0 3? -? -/ -3

    ( -- -1 9 0 ? 2

    D / - -1 -9 -9 -3

    ) 0 -3 -- 4 -9 -1

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    4

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    *wnership 6ost*wnership 6ost

    '($')

    1(31)

    2(2')

    3(11)

    1(2) #12

    2 (1) #22 #13

    3 (1') #3' #21 #1'

    $ ($) #3% #2 #1% #

    Age at #urchase'

    ($')1

    (31)2

    (2')3

    (11)

    1(2) 3

    2 (1) $

    3 (1') 13 1' %

    $ ($) 22 1 1*

    Age at #urchase

    aintenanceaintenance

    6ost6ost

    JearlyJearly

    &otal 6ost&otal 6ost

    '($')

    1(31)

    2(2')

    3(11)

    1(2) 1*

    2 (1) 1$!* 1

    3 (1') 1$!31$!3 1*!* 1%

    $ ($) 1$!* 1*!3 1*!* 1%

    Age at #urchase

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    3omparing Producti%it*

    Two e

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    Equipment A

    6t re

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    Equipment #

    6t re2;---

    Profit = 2-;---

    ou need to in%est !+-;--- to get 2-;--- per *ear for 1+.2 *ears

    P = 2----#1+.2/!+---- = &.-!

    Therefore; # is t$e best proposition.

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    If you could some-o. determine precisely .-at .ould -appen as a result of

    c-oosing eac- option in a decision/ making business decisions .ould be easy0 oucould simply calculate t-e 2alue of eac- competing option and select t-e one .it-t-e -ig-est 2alue0

    In t-e real .orld/ decisions are not 3uite t-is simple0 4o.e2er/ t-e process ofdecision5making stillre3uires c-oosing t-e most 2aluable option55most 2aluablebeing/ in t-is case/ t-e option t-at -as t-e -ig-estExpected Monetary Value6)M78/a measure of probabilistic 2alue0

    Suppose you are gi2en t-e opportunity to play a simple game0 " friend flips a coin0If it comes up -eads/ you .in 910 If it comes up tails/ you .in not-ing0 -at is t-e2alue of t-is game to you; Stated anot-er .ay/ -o. muc- .ould you pay to playt-is game;

    )ac- time you play t-e game you -a2e a +< c-ance of .inning 91 and a +