CHAPTER 5 Modelling and Analysis 1 1. Modelling and Analysis 2 Major DSS component Model base and model management CAUTION Familiarity with major ideas

CHAPTER 5

Modelling and Analysis 1

1

Modelling and Analysis

2

Major DSS componentModel base and model managementCAUTION

Familiarity with major ideasBasic concepts and definitions Tool--influence diagramModel directly in spreadsheets

Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th editionCopyright 2001, Prentice Hall, Upper Saddle River, NJ

Modelling and Analysis

3

Structure of some successful models and methodologiesDecision analysisDecision treesOptimizationHeuristic programming Simulation

New developments in modelling tools / techniques

Important issues in model base management

Modelling and Analysis Topics

4

Modelling for MSS Static and dynamic models Treating certainty, uncertainty, and risk Influence diagrams MSS modelling in spreadsheets Decision analysis of a few alternatives (decision tables and trees) Optimization via mathematical programming Heuristic programming Simulation Multidimensional modelling -OLAP Visual interactive modelling and visual interactive simulation Quantitative software packages - OLAP Model base management

Modelling for MSS

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Key element in most DSS Many classes of modelsSpecialized techniques for each modelAllows for rapid examination of alternative solutionsMultiple models often included in a DSSTrend toward transparency

Necessity in a model-based DSSCan lead to massive cost reduction / revenue increases

Good Examples of MSS Models

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DuPont rail system simulation model (opening vignette)Procter & Gamble optimization supply chain

restructuring models (see presentation pgscredesign.ppt)Scott Homes AHP select a supplier model IMERYS optimization clay production model

Dupont Simulates Rail Transportation System and Avoids Costly Capital Expense Vignette

Promodel simulation created representing entire transport system

Applied what-if analysesVisual simulationIdentified varying conditionsIdentified bottlenecksAllowed for downsized fleet without downsizing

deliveries

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Major Modelling Issues

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Problem identification Environmental analysisVariable identificationForecastingMultiple model useModel categories or selection (Table 5.1)Model managementKnowledge-based modelling


Static and Dynamic Models

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Static AnalysisSingle snapshot

Dynamic AnalysisDynamic modelsEvaluate scenarios that change over timeTime dependentTrends and patterns over timeExtend static models

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Treating Certainty, Uncertainty, and Risk

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Certainty Models

Uncertainty

Risk


Influence Diagrams

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Graphical representations of a modelModel of a modelVisual communicationSome packages create and solve the mathematical modelFramework for expressing MSS model relationships

Rectangle = a decision variable

Circle = uncontrollable or intermediate variable

Oval = result (outcome) variable: intermediate or final

Variables connected with arrows

Example (Figure 5.1)


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FIGURE 5.1 An Influence Diagram for the Profit Model.

~Amount used in advertisement

Profit

Income

Expense

Unit Price

Units Sold

Unit Cost

Fixed Cost


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Analytica Influence Diagram of a Marketing

Problem: The Marketing Model

http://www.youtube.com/watch?v=dSzvuMGJTlk

MSS Modelling in Spreadsheets

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Spreadsheet: most popular end-user modelling toolPowerful functionsAdd-in functions and solversImportant for analysis, planning, modellingProgrammability (macros)

(More)


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What-if analysisGoal seekingSimple database managementSeamless integrationMicrosoft Excel Lotus 1-2-3Excel spreadsheet static model example of a simple loan

calculation of monthly payments (Figure 5.3)Excel spreadsheet dynamic model example of a simple

loan calculation of monthly payments and effects of prepayment

http://www.youtube.com/watch?v=z7pjvTwoz8I&feature=related

MSS Modelling in Spreadsheets

Decision Analysis of Few Alternatives

(Decision Tables and Trees)

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Single Goal Situations

Decision tables

Decision trees


Decision Tables

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Investment example

One goal: maximize the yield after one year

Yield depends on the status of the economy

(the state of nature)Solid growthStagnationInflation


Possible Situations

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1. If solid growth in the economy, bonds yield 12%; stocks 15%; time deposits 6.5%

2. If stagnation, bonds yield 6%; stocks 3%; time deposits 6.5%

3. If inflation, bonds yield 3%; stocks lose 2%; time deposits yield 6.5%


View Problem as a Two-Person Game

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Payoff Table 5.2

Decision variables (alternatives)

Uncontrollable variables (states of economy)

Result variables (projected yield)


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Table 5.2: Investment Problem Decision Table Model

States of Nature

Solid Stagnation Inflation

Alternatives Growth

Bonds 12% 6% 3%

Stocks 15% 3% -2%

CDs 6.5% 6.5% 6.5%


Treating Uncertainty

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Optimistic approach

Pessimistic approach


Treating Risk

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Use known probabilities (Table 5.3)

Risk analysis: compute expected values

Can be dangerous


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Table 5.3: Decision Under Risk and Its Solution

Solid Stagnation Inflation ExpectedGrowth Value

Alternatives .5 .3 .2

Bonds 12% 6% 3% 8.4% *

Stocks 15% 3% -2% 8.0%

CDs 6.5% 6.5% 6.5% 6.5%


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Decision Trees

Other methods of treating riskSimulationCertainty factorsFuzzy logic

Multiple goals

Yield, safety, and liquidity (Table 5.4)

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Table 5.4: Multiple Goals

Alternatives Yield Safety Liquidity

Bonds 8.4% High High

Stocks 8.0% Low High

CDs 6.5% Very High High


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Table 5.5: Discrete vs. Continuous Probability

Distribution

Daily Discrete Continuous

Demand Probability

5 .1 Normally distributed with

6 .15 a mean of 7 and a

7 .3 standard deviation of 1.2

8 .25

9 .2


Documents

CHAPTER 5 Modelling and Analysis 1 1. Modelling and Analysis 2 Major DSS component Model base and model management CAUTION Familiarity with major ideas