decision analysis
Rust99
Lesson5.pdf
DECISION TREES AND INFLUENCE DIAGRAMS
BBA312 – Decision Analysis
DIEGO NAVARRA, DR. [email protected]
Symbols used on decision trees
Decision node
Chance node
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Constructing a decision tree: An initial tree..
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
A new decision tree for the food- processor problem
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Decision trees and utility: The engineer’s utility function
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Applying rollback to utilities
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
The Pearson-Tukey approximation method
The method is based on earlier work by Pearson and Tukey and requires three estimates to be made by the decision maker:
I. The value in the distribution which has a 95% chance of being exceeded. This value is allocated a probability of 0.185.
II. The value in the distribution which has a 50% chance of being exceeded. This value is allocated a probability of 0.63.
III. The value in the distribution which has only a 5% chance of being exceeded. This value is also allocated a probability of 0.185.
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
The extended Pearson-Tukey approximation method
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Eliciting decision structure: One representation of the calculator problem
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Towards a correct representation of the calculator problem?
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Phases of a decision analysis
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
Eliciting decision-tree representations: Definitions used in influence diagrams
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
An example of an influence diagram
Decision tree derived from influence diagram
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
• Handbook of Decision Analysis, by Gregory S. Parnell, Terry Bresnick, Steven N. Tani, and Eric R. Johnson (2013); Publisher John Wiley & Sons, Chapter 11
• Decision Analysis for Management Judgment, 4th ed., Goodwin & Wright, Chapter 7
Recommended reading
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
BBA312 – Decision Analysis (Lesson 5) Dr Diego Navarra: [email protected]
• Howard, R.A. (1988) Decision Analysis: Practice and Promise, Management Science, 34(6), 679–695
• Keefer, D.L. and Bodily, S.E. (1983) Three Point Approximations for Continuous Random Variables, Management Science, 29(5), 595–609..
• Pearson, E.S. and Tukey, J.W. (1965) Approximating Means and Standard Deviations Based on Distances between Percentage Points of Frequency Curves, Biometrika, 52(3/4), 533–546.
• Von Winterfeldt, D.V. (1980) Structuring Decision Problems for Decision Analysis, Acta Psychologica, 45, 73–93.
• Fischhoff, B. (1980) Decision Analysis: Clinical Art or Clinical Science?, in L. Sjoberg, T. Tyszka and J.A. Wise (eds), Human Decision Making, Bodafors, Doxa.
• Keeney, R. (1980) Decision Analysis in the Geo-technical and Environmental Fields, in L. Sjoberg, T. Tyszka and J.A. Wise (eds), Human Decision Making, Bodafors, Doxa.
• Humphreys, P. (1980) Decision Aids: Aiding Decisions, in L. Sjoberg, T. Tyszka and J.A. Wise (eds), Human Decision Making, Bodafors, Doxa.
References
