Marakas-Ch04

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Marakas: Decision Support Systems, 2nd Edition 2003, Prentice-Hall Capter ! - "

Chapter 4:

Modeling Decision Processes

Decision Support Systems in the

21st

Century, 2nd

Editionby George M. Marakas


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Marakas: Decision Support Systes, 2nd Edition !2""#, Prentice$%all

Chapter 4 $ 2

4-1: Defining the Problem and Its Structure

& 'ully 'ored proble stateent contains three

key coponents:

( )he current state o' a''airs( )he desired state o' a''airs

( & stateent o' the central ob*ecti+es-

that distinguish the to


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Problem Definition Errors

/ailing to identi'y and de'ine the proble 'ully

ay result in a great solution that does not

sol+e the right proble& coon error: preature 'ocus on the set

o' solutions rather than the proble itsel'

)he decision aker ay be le't ith a

solution looking 'or a proble to sol+e


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Chapter 4 $ 4

Problem Scope

)he proble ay be orth sol+ing but the

scope is beyond the a+ailable resources or

tie constraints0n such cases, the scope ust be reduced to

a 'ocus that allos a solution

1ne ethod to liit the scope is to identi'y its

breadth by asking uestions about people

in+ol+ed, cost and agnitude


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Chapter 4 $ 3

Problem Structure

Design o' proble structure is siilar to designo' any other entities

hat is the 'inal appearance5hat are the eleental details5hat are the relationships beteen those

eleents5

6egardless o' conte7t, a proble structure canbe described in ters o' choices,uncertainties and ob*ecti+es


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Chapter 4 $ 8

Problem Structure (cont.)

Choices:there are alays at least to

alternati+es one is 9do nothing-

Uncertainties:situations beyond the directcontrol o' the decision aker; their indi+idual

probability o' occurrence is only estiable

ithin a certain range

Objectives: ethods o' establishing the

criteria used to easure the +alue o' the

outcoe


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Chapter 4 $

&ommon Decision Structures

Basic Risky Decision:decision aker takes a

choice in the 'ace o' uncertainty. Success is

a 'unction o' the choice and outcoe.Certainty:a ultiple$ob*ecti+e decision ith

little risk. Success is a 'unction o' the trade$

o'' beteen ob*ecti+es.

Sequential:se+eral risky decisions o+er tie.

Earlier outcoes ay a''ect later choices.


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Chapter 4 $ ?"

4-': Decision odels

Decision odels can be classi'ied in a nuber

o' ays:

0s tie a 'actor5 Models that do notinclude tie are 9static +ersus 9dynaic

hat is the techniue@s atheatical

'ocus5 Soe abstract odel types are

deterinistic, stochastic, siulation and

doain speci'ic


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Chapter 4 $ ??

odel &lassification E#amples

Deterministic: linear prograing, production

planning

Stochastic: ueuing theory, linear regressionanalysis

Simulation: production odeling, transportation

analysis

Domainspeci!ic:E1A, technology di''usion,

eteorological odels


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Chapter 4 $ ?2

&onceptual odels

& 'oral atheatical approach is not alays

appropriate

Conceptual odels are 'orulated under thenotion that e+en though all probles are

uniue, no proble is copletely ne

Decision akers can recall and cobine a

+ariety o' past e7periences to create an

accurate odel o' the current situation


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Chapter 4 $ ?#

4-: *pes of Probabilit*

)hree reuireents o' probability:

?. &ll probabilities are in the range " to ?

2. )he probabilities o' all outcoes o' ane+ent ust add up to the probability o'

their union

#. )he total probability o' a coplete set o'outcoes ust eual ?


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+o" ,re Probabilities enerated

"on#run !requency:ith enough 9history,

you can estiate an e+ent@s probability by its

relati+e 'reuencySubjective:probability represents an

indi+idual@s 9degree o' belie' that an e+ent

ill occur

"o#ic:a probability ay be deri+able, but its

accuracy ay not be acceptable


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Chapter 4 $ ?3

4-4: echni%ues for

/orecasting ProbabilitiesDirect probability !orecastin#B an e7pert is

siply asked to estiate the chance that an

outcoe ill occurO$$s !orecastin#B a series o' bets are

proposed to deterine ho strongly the

bettor 'eels an e+ent ill occur

Comparison !orecastin#B siilar to odds

'orecasting e7cept that one gae has knon

probabilities


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Decomposing &omple# Probabilities

Probabilities 'or cople7 e+ents ay be ore

easily generated by using conditional

probabilities ithin subsets o' the e+ents

/or e7aple, it ay be easier to 'orecast sales

o' a eather$related product by 'orecasting

sales under good eather, then bad eather

and then considering the probability o' bad

eather


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Chapter 4 $ ?

2alue ,nal*sis

e alays need to be concerned that enough

reliable in'oration is a+ailable to ake a

success'ul decision.e can deterine ho uch e are illing to

pay 'or better in'o by coputing its e7pected

+alue.

)his in+ol+es a coparison o' the e7pectedreturn ith the in'o to the e7pected return

ithout the in'o.

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Marakas-Ch04