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Analytic Hierarchy Process
• Multiple-criteria decision-making
• Real world decision problems
– multiple, diverse criteria
– qualitative as well as quantitative information
Comparing apples and oranges?
Spend on defence or agriculture?
Open the refrigerator - apple or orange?
AHP
• Information is decomposed into a hierarchy of
alternatives and criteria
• Information is then synthesized to determine
relative ranking of alternatives
• Both qualitative and quantitative information
can be compared using informed judgements
to derive weights and priorities
Example: Car Selection
• Objective
– Selecting a car
• Criteria
– Style, Reliability, Fuel-economy Cost?
• Alternatives
– Civic Coupe, Saturn Coupe, Ford Escort,
Mazda Miata
Hierarchical tree
S t y le R e lia b ilit y F u e l E c o n o m y
S e le c t in g
a N e w C a r
- Civic
- Saturn
- Escort
- Miata
- Civic
- Saturn
- Escort
- Miata
- Civic
- Saturn
- Escort
- Miata
Ranking of criteria
• Weights?
• AHP
– pair-wise relative importance
[1:Equal, 3:Moderate, 5:Strong, 7:Very strong, 9:Extreme]
Style Reliability Fuel Economy
Style
Reliability
Fuel Economy
1/1 1/2 3/1
2/1 1/1 4/1
1/3 1/4 1/1
Ranking of priorities
• Eigenvector [Ax = λx]
Iterate
1. Take successive squared powers of matrix
2. Normalize the row sums
Until difference between successive row sums is
less than a pre-specified value
1 0.5 3
2 1 4
0.333 0.25 1.0
3.0 1.75 8.0
5.3332 3.0 14.0
1.1666 0.6667 3.0
squared
Row sums
12.75
22.3332
4.8333
39.9165
Normalized
Row sums
0.3194
0.5595
0.1211
1.0
• New iteration gives normalized row sum
0.3196
0.5584
0.1220
• Difference is: -
0.3194
0.5595
0.1211
0.3196
0.5584
0.1220
=
- 0.0002
0.0011
- 0.0009
Preference
• Style .3196
• Reliability .5584
• Fuel Economy .1220
S t y le
. 3 1 9 6
R e lia b ilit y
. 5 5 8 4
F u e l E c o n o m y
. 1 2 2 0
S e le c t in g
a N e w C a r
1 .0
Ranking alternatives
Style
Civic
Saturn
Escort
1/1 1/4 4/1 1/6
4/1 1/1 4/1 1/4
1/4 1/4 1/1 1/5
Miata 6/1 4/1 5/1 1/1
Civic Saturn Escort Miata
Miata
Reliability
Civic
Saturn
Escort
1/1 2/1 5/1 1/1
1/2 1/1 3/1 2/1
1/5 1/3 1/1 1/4
Miata 1/1 1/2 4/1 1/1
Civic Saturn Escort Miata
.1160
.2470
.0600
.5770
Eigenvector
.3790
.2900
.0740
.2570
Fuel Economy
(quantitative
information)
Civic
Saturn
Escort
MiataMiata
34
27
24
28
113
Miles/gallon Normalized
.3010
.2390
.2120
.2480
1.0
S t y le
. 3 1 9 6
R e lia b ilit y
. 5 5 8 4
F u e l E c o n o m y
. 1 2 2 0
S e le c t in g
a N e w C a r
1 .0
- Civic .1160
- Saturn .2470
- Escort .0600
- Miata .5770
- Civic .3790
- Saturn .2900
- Escort .0740
- Miata .2570
- Civic .3010
- Saturn .2390
- Escort .2120
- Miata .2480
Ranking of alternatives
Style Reliability Fuel
Economy
Civic
Escort
MiataMiata
Saturn
.1160 .3790 .3010
.2470 .2900 .2390
.0600 .0740 .2120
.5770 .2570 .2480
*
.3196
.5584
.1220
=
.3060
.2720
.0940
.3280
Handling Costs
• Dangers of including Cost as another criterion
– political, emotional responses?
• Separate Benefits and Costs hierarchical trees
• Costs vs. Benefits evaluation
– Alternative with best benefits/costs ratio
Cost vs. Benefits
• MIATA $18K .333 .9840
• CIVIC $12K .222 1.3771
• SATURN $15K .2778 .9791
• ESCORT $9K .1667 .5639
Cost
Normalized
Cost
Cost/Benefits
Ratio
Complex decisions
•Many levels of criteria and sub-criteria
• Application areas
– strategic planning
– resource allocation
– source selection, program selection
– business policy
– etc., etc., etc..
• AHP software (ExpertChoice)
– computations
– sensitivity analysis
– graphs, tables
• Group AHP

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Analyze Complex Decisions with the Analytic Hierarchy Process (AHP

  • 1. Analytic Hierarchy Process • Multiple-criteria decision-making • Real world decision problems – multiple, diverse criteria – qualitative as well as quantitative information Comparing apples and oranges? Spend on defence or agriculture? Open the refrigerator - apple or orange?
  • 2. AHP • Information is decomposed into a hierarchy of alternatives and criteria • Information is then synthesized to determine relative ranking of alternatives • Both qualitative and quantitative information can be compared using informed judgements to derive weights and priorities
  • 3. Example: Car Selection • Objective – Selecting a car • Criteria – Style, Reliability, Fuel-economy Cost? • Alternatives – Civic Coupe, Saturn Coupe, Ford Escort, Mazda Miata
  • 4. Hierarchical tree S t y le R e lia b ilit y F u e l E c o n o m y S e le c t in g a N e w C a r - Civic - Saturn - Escort - Miata - Civic - Saturn - Escort - Miata - Civic - Saturn - Escort - Miata
  • 5. Ranking of criteria • Weights? • AHP – pair-wise relative importance [1:Equal, 3:Moderate, 5:Strong, 7:Very strong, 9:Extreme] Style Reliability Fuel Economy Style Reliability Fuel Economy 1/1 1/2 3/1 2/1 1/1 4/1 1/3 1/4 1/1
  • 6. Ranking of priorities • Eigenvector [Ax = λx] Iterate 1. Take successive squared powers of matrix 2. Normalize the row sums Until difference between successive row sums is less than a pre-specified value
  • 7. 1 0.5 3 2 1 4 0.333 0.25 1.0 3.0 1.75 8.0 5.3332 3.0 14.0 1.1666 0.6667 3.0 squared Row sums 12.75 22.3332 4.8333 39.9165 Normalized Row sums 0.3194 0.5595 0.1211 1.0 • New iteration gives normalized row sum 0.3196 0.5584 0.1220 • Difference is: - 0.3194 0.5595 0.1211 0.3196 0.5584 0.1220 = - 0.0002 0.0011 - 0.0009
  • 8. Preference • Style .3196 • Reliability .5584 • Fuel Economy .1220 S t y le . 3 1 9 6 R e lia b ilit y . 5 5 8 4 F u e l E c o n o m y . 1 2 2 0 S e le c t in g a N e w C a r 1 .0
  • 9. Ranking alternatives Style Civic Saturn Escort 1/1 1/4 4/1 1/6 4/1 1/1 4/1 1/4 1/4 1/4 1/1 1/5 Miata 6/1 4/1 5/1 1/1 Civic Saturn Escort Miata Miata Reliability Civic Saturn Escort 1/1 2/1 5/1 1/1 1/2 1/1 3/1 2/1 1/5 1/3 1/1 1/4 Miata 1/1 1/2 4/1 1/1 Civic Saturn Escort Miata .1160 .2470 .0600 .5770 Eigenvector .3790 .2900 .0740 .2570
  • 11. S t y le . 3 1 9 6 R e lia b ilit y . 5 5 8 4 F u e l E c o n o m y . 1 2 2 0 S e le c t in g a N e w C a r 1 .0 - Civic .1160 - Saturn .2470 - Escort .0600 - Miata .5770 - Civic .3790 - Saturn .2900 - Escort .0740 - Miata .2570 - Civic .3010 - Saturn .2390 - Escort .2120 - Miata .2480
  • 12. Ranking of alternatives Style Reliability Fuel Economy Civic Escort MiataMiata Saturn .1160 .3790 .3010 .2470 .2900 .2390 .0600 .0740 .2120 .5770 .2570 .2480 * .3196 .5584 .1220 = .3060 .2720 .0940 .3280
  • 13. Handling Costs • Dangers of including Cost as another criterion – political, emotional responses? • Separate Benefits and Costs hierarchical trees • Costs vs. Benefits evaluation – Alternative with best benefits/costs ratio
  • 14. Cost vs. Benefits • MIATA $18K .333 .9840 • CIVIC $12K .222 1.3771 • SATURN $15K .2778 .9791 • ESCORT $9K .1667 .5639 Cost Normalized Cost Cost/Benefits Ratio
  • 15. Complex decisions •Many levels of criteria and sub-criteria
  • 16. • Application areas – strategic planning – resource allocation – source selection, program selection – business policy – etc., etc., etc.. • AHP software (ExpertChoice) – computations – sensitivity analysis – graphs, tables • Group AHP

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