3. DECISION TREE ANALYSIS
•A decision tree is a graphic device of decision
making process.
•It is a graphical presentation of the various
alternatives.
•It is also known as tree diagram.
4. DECISION TREE
• A decision tree is a decision support tool that uses a tree like
graph or model of decision and their possible consequences
,including chance event outcomes resource costs and utility.
• It is one way to display an algorithm.
• Decision tree are commonly used in operation research ,
specially in decision analysis to help identify a strategy most
likely to reach a goal.
5. TYPES OF NODES
• Decision nodes- commonly represented by square.
• Chance nodes- represented by circles.
• End nodes- represented by triangle.
• A DECISION tree has burst nodes.
6. EXAMPLE
• A GLASS FACTORY THAT SPECIALIZEZ IN CRYSTAL IS DEVELOPING A
SUBSTANTIAL BACK LOG AND FOR THIS THE FIRM MANAGEMENT IS
CONSIDERING THREE COURCES OF ACTION; THE CORRECT CHOICES DEPENDS
LARGELY UPON THE FUTURE DEMAND , WHICH MAY BE LOW MEDIUM OR HIGH
• 1 SHOW THIS DECISION SITUATION IN THE FORM OF A DECION TREE
• 2 INDICATE THE MOST PREFFERED DECISION
• 3 CORRESPONDING EXPECTED VALUE
7.
8. EXPECTED MONETARY VALUE
• EMV=(0.1x10)+(o.50x50)+(0.40x50)=46
• EMV=(0.10x20)+(0.50x60)+(0.40x100)=68
• EMV=(0.10x150)+(0.50x20)+(0.40x200)=75
Highest EMV will be selected so,S3 will be selected
9.
10. TO FIND OUT MOST PREFERRED ALTERNATIVE
• ALWAYS FIND OUT
• EMV
11. EXPECTED VALUE OF SAMPLE INFORMATION
• WAY OF MEASURING MARKET INFORMATION.
• IS INCREASE IN EXPECTED VALUE RESULTING FROM THE SAMPLE INFORMATION.
• Evsi=(ev with SI +COST) – (EV WITHOUT SI)
• (75+200)-(46)
• 229
• 229 ARE NEED FOR MARKET STUDY
12. EFFICIENCY OF SAMPLE INFORMATION
•Efficiency of sample information = EVSI/EVPI
x 100%
•If the sample information was perfect then
the efficiency would be 100%
•EVSI / EVPI x100%
