Midterm Exam - DSC-8240 Murugan Chellasamy
Download
Report
Transcript Midterm Exam - DSC-8240 Murugan Chellasamy
Midterm Exam - DSC-8240
Murugan Chellasamy
Cases
Cold
Fusion
Prescribed Fire
GPC
Strenlar
Cold Fusion
Objective
Hierarchies
Variables & Measures
Problem Structuring
Consequence
Table
Influence Diagram
Decision Tree
Mathematical
Model - NA
Solutions & Sensitivity
Cases
Cold Fusion - Objective Hierarchies
Objective Hierarchy
Maximize Wealth/Self Satisfaction
Maximize Economical Effects
Maximize Personal Satisfaction
Cold Fusion - Variables & Measures
Decision Variables:
Chance Variables
Good for the Society
Bad for the Society
Bill Passed
Bill Rejected
High Political Value
Low Political Value
Fusion Works
Fusion Fails
Economically Feasible
Economically Infeasible
Consequence
Actually Helps Society
Does not make any difference
Cold Fusion - Consequence Table
Cold Fusion - Consequence Table
Eco/Soc Effects Bill
Political Value Fusion
Good
Passed
High
Works
Works
Fails
Rejected
Low
No Effect
Bad
Passed
High
Rejected
Low
Works
Works
Fails
No Effect
Feasibility
Feasible
Infeasible
No Effect
No Effect
Feasible
Infeasible
No Effect
No Effect
Cold Fusion - Influence Diagram
High Political
Value
High/Low
Bill
Passed/Rejected
Good /Bad
For
Society
High Satisfaction
Fusion
Works/Fails
Cold Fusion - Decision Tree
Cold Fusion - Solutions & Sensitivity
I believe the fate of this bill will be determined by the relative publicity it can generate
to help the politicians and the scientists. It would be very hard to determine the
economic and social benefits derived from Cold Fusion. It could be very beneficial
to the society but if it meant that we would have to stop using the existing sources
of energy, it may cause severe economic strains. On the other hand it may help the
economy but may create problems to the society by making destructive technology
available at a cheaper cost. Even if the bill gets passed, it may not be feasible to use
this technology to reap the desired benefits.
Prescribed Fire
Objective
Hierarchies
Variables & Measures
Problem Structuring
Consequence
Table
Influence Diagram
Decision Tree
Mathematical
Model
Solutions & Sensitivity
Cases
Prescribed Fire - Objective Hierarchies
Objective Hierarchy
Cost Efficient Burning
Different Methods
Associated Problems
Prescribed Fire - Variables & Measures
Decision Variables:
Chance Variables
Burn Slash
YUM
Controlled Fire
Uncontrollable Fire - Escaped Fire
Uncontrollable Fire - Problems
Consequence
Cost Efficient Burn
Escaped Fire
Low Cost Burn
Medium Cost Burn
High Cost Burn
Prescribed Fire - Consequence Table
Method
Slash Burn
YUM
Prescribed Fire - Per Acre
Burn Result
Cost
Controlled
Minimal
Escaped Fire
Substantial
Uncontrolled
Low
Medium
High
Controlled
Escaped Fire
Uncontrolled
Minimal
Substantial
Low
Medium
High
Amount
$85
$1,000
$125
$200
$500
$185
$1,000
$225
$300
$600
Prescribed Fire - Influence Diagram
Uncontrolled
Fire
Controlled
Fire
Low
High
Medium
Costs
Choose
Method
Cost Efficient
Burn
Prescribed Fire - Decision Tree
Prescribed Fire Solutions & Sensitivity
Given the scenario’s, YUM seems to be the most cost efficient method .
GPC
Objective
Hierarchies
Variables & Measures
Problem Structuring
Consequence
Table
Influence Diagram
Decision Tree- NA
Mathematical
Model
Solutions & Sensitivity
Cases
GPC - Objective Hierarchies
Objective Hierarchy
Maximize Returns
Evaluate Risk/Return
Consider Different Scenarios
Study Options
GPC - Variables & Measures
Decision Variables:
Chance Variables
Product A
Product B
Product C
Delay in production
Price
Sales
Market Share
Consequence
Increased Market Share
Lose Market Share
Increased Return
Reduced Margin
GPC - Consequence Table
Product
A
B
C
GPC- Consequence Table
Delay
Price
Sales
Yes
High
High Sales
Low Sales
Low
High Sales
Low Sales
No
High
High Sales
Low Sales
Low
High Sales
Low Sales
Yes
High
Medium
Low
Return (Millions)
$5.00
($0.50)
$3.50
$1.00
$8.00
$0.00
$4.50
$1.50
$8.00
$4.00
$0.00
$1.00
GPC - Influence Diagram
Sales
Product
Delay
Maximize
Return
Choose
Product
GPC - Mathematical Model
Mathematical Models
EMVA delay = max (((0.3 * 5) + (0.7 * (-0.5))), ((0.5 * 3.5) + (0.5 * 1)))
EMVA no delay = max (((0.4 * 8) + (0.6 * 0)), ((0.5 * 4.5) + (0.5 * 1.5)))
EMVA = max (EMVA delay, EMVA no delay )
EMVB = (0.38 * 8) + (0.12 * 4) + (0.5 * 0)
EMVC = 1.0
EMV Optimal Decision = max( EMVA, EMVB, EMVC )
GPC - Solutions & Sensitivity
I was not able to get DPL to draw a decision tree. In any event, if we had more time and
information we could have done more analysis. We could have used excel to set up
a solver with constraints (upper and lower limits on probability) for products A &
B to get a maximized return. We could also have set up a regression model with
sales as the dependent variable with delay and price as independent variables to
project profits with certain level of confidence. But, given the information we have,
I would suggest we go with product B since we are a lot more certain about its out
come. The decision will also be impacted by many other factors like the GPC’s
financial strength and its position in the market etc.
Strenlar
Objective
Hierarchies
Variables & Measures
Problem Structuring
Consequence
Table
Influence Diagram
Decision Tree
Mathematical
Model
Solutions & Sensitivity
Cases
Strenlar - Objective Hierarchies
Objective Hierarchy
Maximize Self Satisfaction
One of Many
Against The World
Financial/Emotional
Stability
Uncertainity
Gauranteed Lifestyle
Safety
Self Esteem
Pride
Strenlar - Variables & Measures
Decision Variables:
Chance Variables
Accept Offer
Reject Offer
Financial/ Physical/ Emotional State
Peer & Social Pressure
Future
Consequence
Rich & Happy
Broke & Miserable
Self Esteem??
Strenlar - Consequence Table
Strenlar - Consequence
Offer
Lawsuit Process
Accept
None
Works
Fails
Table
Fin State
Good
Good
Reject
Good
Bad
Bad
Bad
Win
Lose
Works
Fails
Works
Fails
Strenlar - Influence Diagram
Emotional
State
Financial
State
Physical
State
Accept/Reject
Offer
Maximize
Satisfaction
Strenlar - Decision Tree
Strenlar - Mathematical Model
The following diagram, done in Excel, accompanies the mathematical model used by Fred:
EMV Lawsuit = (0.6 * ((0.8 * 8,000) + (0.2 * (-200)))) + (0.4 * (-220))
EMVPI job = (0.8 * 2,443) + (0.2 * 343)
EMV lump sum = (0.8 * 1,252) + (0.2 * 500)
EMV Optimal decision = max ( EMV Lawsuit, EMVPI job, EMV lump sum )
Strenlar Solutions & Sensitivity
Fred’s position is unenviable. His decision will be influenced by how he feels about
himself. I don’t think we can help him make a decision based on the financial
outcomes. If Fred was a corporation, we could argue that he should reject the offer
and take them to court since maximizing the value of the assets would be his only
goal.