Module 4
1 / 33

Module 4 Modeling Decisions: MAKING CHOICES - PowerPoint PPT Presentation

  • Updated On :

Module 4 Modeling Decisions: MAKING CHOICES. Topics: Creating case study decision tree Solving a decision tree Risk profiles Dominance of alternatives Attributes and scales Using multiple objectives. Introduction. Module 3: Structure values and objectives Identify performance measures

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Module 4 Modeling Decisions: MAKING CHOICES' - shanna

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Slide1 l.jpg

Module 4

Modeling Decisions:



Creating case study decision tree

Solving a decision tree

Risk profiles

Dominance of alternatives

Attributes and scales

Using multiple objectives

Introduction l.jpg

  • Module 3:

    • Structure values and objectives

    • Identify performance measures

    • Structure decision tree and influence diagram models

  • Module 4:

    • Solve decision trees

    • Approach for multiple objectives

  • Module 4 software tutorial

Making choices learning objectives l.jpg
Making ChoicesLearning Objectives

  • Create decision tree from case study

  • Solve a decision tree

    • Expected value preference criterion

  • Create and interpret

    • Risk profiles

    • Cumulative risk profiles

  • Concept of dominance

    • Definition and identification

    • Decision problem simplification

Making choices learning objectives4 l.jpg
Making ChoicesLearning Objectives

  • Develop

    • Constructed attributes

    • Constructed scales

  • Formulate multiple objectives problems

    • Common scales

    • Trade–off weights

    • Composite consequences

Making choices l.jpg
Making Choices

  • Analysis of structured problems

    • graphing

    • calculating

    • examining results

Texaco versus pennzoil l.jpg
“Texaco versus Pennzoil”

  • Pennzoil and Getty Oil agreed to a merger

  • Texaco made better offer to Getty

  • Getty reneged on Pennzoil and sold to Texaco

  • Pennzoil sued Texaco for interference

  • Pennzoil won and was awarded the $11.1 billion

Texaco versus pennzoil7 l.jpg
“Texaco versus Pennzoil”

  • Texaco appealed; award reduced to $10.3 billion

  • Texaco threatened bankruptcy if Pennzoil filed liens

  • Texaco also threatened to take case to Supreme Court

Texaco versus pennzoil8 l.jpg
“Texaco versus Pennzoil”

  • Texaco offered to settle out of court by paying Pennzoil $2 billion

  • Pennzoil believed fair settlement between $3 and $5 billion

Texaco versus pennzoil9 l.jpg
“Texaco versus Pennzoil”

  • What should Pennzoil do?

    • Accept $2 billion settlement

    • Make counteroffer

  • Assume objective is to maximize settlement

Decision trees and expected monetary value l.jpg
Decision Trees and Expected Monetary Value

  • Expected Monetary Value (EMV); i.e., select alternative with highest expected value

  • “Folding back the tree” or “rolling back” procedure

Decision trees and expected monetary value11 l.jpg
Decision Trees and Expected Monetary Value

Folding Back:

  • Start at the endpoints of the branches on the far right-hand-side and move to the left

  • Calculate expected values at a chance node

  • Choose the branch with the highest value or expected value at a decision node.

Expected monetary value l.jpg
Expected Monetary Value

  • Weighted average of outcomes at chance node

  • Sum of the product of each outcome and its probability

Pennzoil s decision tree l.jpg
Pennzoil’s Decision Tree

  • Pennzoil’s final decision tree

    figure 4.7

  • What has been decided?

    • Pennzoil should reject Texaco’s offer and make a $5 billion counteroffer

    • If Texaco then makes a $3 billion counteroffer, Pennzoil should take its chances in court

Solving influence diagrams l.jpg
Solving Influence Diagrams

  • More cumbersome than decision trees

  • Conversion to symmetric decision tree

  • Software packages used

Risk profiles l.jpg
Risk Profiles

  • Graph illustrating chances of possible payoffs or consequences

  • One profile for each strategy

    graph 4.18

Risk profiles16 l.jpg
Risk Profiles

  • Creation is straightforward process, but tedious

  • Can create for strategies and specific sequences

  • Only strategies for first one or two decisions examined

Risk profiles17 l.jpg
Risk Profiles

  • Three steps to follow:

    • Determine probabilities of paths

    • Determine probabilities of payoffs

    • Create charts for strategies

Dominance l.jpg

  • Dominating alternative always preferred over another alternative

  • Dominating alternative always has higher EV than other alternative

Dominance19 l.jpg

  • May enable elimination of alternatives early in the process

  • Elimination simplifies and reduces cost of the process

Dominance20 l.jpg


  • Inspection

  • Cumulative distribution function

    • Cumulative risk profile

  • Sensitivity analysis

    • Tornado diagram

Attributes and scales l.jpg
Attributes and Scales

Measurement of fundamental objectives

  • Measurement crucial to evaluation of consequences

  • Methods must be consistent with objectives

  • Attributes and attribute scales define measurement

  • Different types of attributes

Attributes and scales22 l.jpg
Attributes and Scales

  • Purpose: Explore attributes and scales

    that measure achievement of


  • Major field of study and in-depth exploration beyond scope of cource

Attributes and scales23 l.jpg
Attributes and Scales

  • Attribute: measure of performance or merit

  • Scale: defined graduated series or specified scheme

  • Scale frequently implicit in attribute definition

Types of attributes l.jpg
Types of Attributes

Keeney identifies three types of attributes:

  • Natural attributes

    • generally known and have common meaning

    • for example, centimeters

  • Constructed attributes

    • created when no natural attributes exists

    • for example, qualitative ratings

  • Proxy attributes

    • indirect measures (either natural or constructed) when no direct measures exist

    • for example, use “sulphur dioxide concentration” for “acid rain damage to sculptures”

Constructed attributes l.jpg
Constructed Attributes

  • Intellectually challenging and demanding

  • Requires depth of knowledge and understanding of decision situation and objectives

  • Three properties

    • measurable: define objective in detail

    • operational: describe possible consequences

    • understandable: no ambiguity

Constructed attributes26 l.jpg
Constructed Attributes

  • Frequently needed and most challenging

  • A constructed attribute of site biological impact

Constructed attributes27 l.jpg
Constructed Attributes

  • Implied scale may not reflect measures needed

  • Nominal values in rank order may not correspond to rational scale

  • For example

    (level 2 – level 1) ?≠? (level 4 – level 3)

  • Use subjective judgment to rate nominal values on rational scale

Constructed attributes28 l.jpg
Constructed Attributes

  • Define constructed attributes from natural attributes

  • Need to compare or combine constructed and natural attributes

  • Convert natural attributes to constructed scale using proportions

Multiple objectives l.jpg
Multiple Objectives

Problems require:

  • Common scale for measurement of consequences

  • Trade–off weights for objectives

  • Single composite consequence

Multiple objectives30 l.jpg
Multiple Objectives

Common scale for consequences:

  • Select common scale

    • May be one used for an objective

    • May be one not already used

    • May be natural or constructed

    • Tendency toward constructed with utility values

  • Convert consequence measures for each objective to common scale

Multiple objectives31 l.jpg
Multiple Objectives

Trade–offs weights:

  • Value between zero and one

  • Sum to unity

  • Consider consequence range

  • Reflect relative importance of objectives

  • Consistent with objectives hierarchy

Multiple objectives32 l.jpg
Multiple Objectives

Composite consequence for final outcomes:

  • Linear combination of individual consequences

  • Trade–off weights are coefficients

Summary l.jpg

  • Creation of decision tree from case study

  • Solution of case study decision tree

  • Construction and use of risk profiles

  • Definition and use of dominance

  • Attributes and attribute scales, particularly constructed attributes

  • Formulation and solution of a multiple objectives problem