SUSTAINABILITY MCDM
MODEL COMPARISONS
Yuan-Sheng Lee, Tamkang University
Hsu-Shih Shih, Tamkang University
David L. Olson, University of Nebraska
European DSI 2014, Kolding, Denmark
SUSTAINABILITY
Tzeng et al. [2005] Energy Policy
• DECISION: select bus type from 12 choices
• Eleven criteria
• Our use:
• Demonstration of features of various multi-criteria methods
European DSI 2014, Kolding, Denmark
Multi-Criteria Models of Sustainability
• Non-dominated Identification
• Lotov et al. [2004]; Bouchery et al. [2012]
• Cardinal weighting
• Equal weights; Tchebychev; Ordinal; SMART; AHP
• Outranking
• ELECTRE; PROMETHEE
• TOPSIS (Technique for Preference by Similarity to the Ideal Solution)
• Min distance to ideal while Max distance from nadir
• Hwang & Yoon [1981]
• TODIM
• From cumulative prospect theory, S-shaped value function
• Gomes & Lima [1992]
European DSI 2014, Kolding, Denmark
Urban Transportation Selection Decision
Select a bus type – CRITERIA (Tzeng et al., 2005)
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Energy supply
Energy efficiency
Air pollution
Noise pollution
Industrial relations
Employment cost
Maintenance cost
Capability of vehicle
Road facility
Speed of traffic
Sense of comfort
European DSI 2014, Kolding, Denmark
TODIM
• Classify multiple criteria into benefits, costs
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STEP 1: DM constructs normalized decision matrix (see next slide)
STEP 2: Value alternatives on each criterion with 0 the worst and 1 the best
STEP 3: Compute matrix of relative dominance
STEP 4: Calculate global measure for each alternative
STEP 5: Rank alternatives by global measures
European DSI 2014, Kolding, Denmark
Part 1:
Bus Type
Energy
Supply
Energy
Efficiency
Air Pollution
Noise
Pollution
Industrial
Relations
Employ Cost
A1 Diesel
0.82
0.59
0.18
0.42
0.58
0.36
A2 CNG
0.77
0.70
0.73
0.55
0.55
0.52
A3 LPG
0.79
0.70
0.73
0.55
0.55
0.52
A4 Hydrogen
0.36
0.63
0.86
0.58
0.51
0.59
A5 Methanol
0.40
0.54
0.69
0.58
0.51
0.52
A6 Elec OpC
0.69
0.76
0.89
0.60
0.72
0.80
A7 Elec Dir
0.77
0.79
0.89
0.59
0.73
0.80
!8 Elec Bat
0.77
0.79
0.89
0.59
0.73
0.80
A9 HybGas
0.77
0.63
0.63
0.52
0.66
0.63
A10 HybDies
0.77
0.63
0.51
0.58
0.66
0.63
A11 HybCNG
0.77
0.73
0.80
0.48
0.63
0.66
A12 HybLPG
0.77
0.73
0.80
0.48
0.63
0.66
European DSI 2014, Kolding, Denmark
Part II
Bus Type
Maintenance
cost
Vehicle
capability
Roads
Traffic speed
Comfort
A1 Diesel
0.40
0.79
0.81
0.82
0.56
A2 CNG
0.53
0.73
0.78
0.66
0.67
A3 LPG
0.53
0.73
0.78
0.66
0.67
A4 Hydrogen
0.74
0.56
0.63
0.53
0.70
A5 Methanol
0.68
0.52
0.63
0.60
0.70
A6 Elec OpC
0.72
0.54
0.35
0.79
0.73
A7 Elec Dir
0.72
0.47
0.44
0.87
0.75
A8 Elec Bat
0.72
0.51
0.48
0.87
0.75
A9 HybGas
0.65
0.67
0.70
0.80
0.74
A10 HybDies
0.65
0.67
0.70
0.80
0.74
A11 HybCNG
0.65
0.67
0.71
0.62
0.78
A12 HybLPG
0.65
0.67
0.71
0.62
0.78
European DSI 2014, Kolding, Denmark
NON-DOMINANCE
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A1 (Diesel Bus)
A3 (LPG Bus) {> A2 on energy supply, = on all others}
A8 (Electric bus with exchangeable batteries) {>A7 on capability, roads}
A6 (Electric bus with opportunity charging)
A9 (Hybrid electric bus with gasoline engine)
A10 (Hybrid electric bus with diesel engine)
A11 (Hybrid electric bus with CNG engine)
A12 (Hybrid electric bus with LPG engine) identical ratings to A11
• A4, A5 dominated by combinations
European DSI 2014, Kolding, Denmark
WEIGHTING
• EQUAL WEIGHTING (LaPlace)
• A8 Electric bus with exchange batteries wins
• A7 a very close second
• PROVIDES FULL RANKING
• Uses cardinal (continuous?) numbers
• TCHEBYCHEV WEIGHTS
• Maximize worst rating – A2 (CNG – dominated by A3), A3(LPG), A9 (Hybrid)
• ORDINAL WEIGHTS (centroid)
• A8 Electric bus with exchange batteries wins
• A7 a very close second
• CARDINAL WEIGHTS (from Tzeng et al. - AHP)
• A8 Electric bus with exchange batteries wins
• A7 a very close second
European DSI 2014, Kolding, Denmark
Simulation
Bus Type (nondominated)
Proportion Won
A1
Diesel
0.005
A3
LPG
0.110
A6
Electric optional charging
A8
Electric battery
0.625
A9
Hybrid gas
0.110
A10
Hybrid diesel
0.045
A11
Hybrid CNG or LPG
0.205
European DSI 2014, Kolding, Denmark
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PROMETHEE
European DSI 2014, Kolding, Denmark
Distance methods
• TOPSIS
• A8 Electric exchange batteries
• A6 Electric optional charge close behind
• A7 Electric direct exchange (dominated solution) close behind
• TODIM
• A8 Electric exchange batteries
• A7 Electric direct exchange (dominated solution) second
• A11/A12 Hybrid CNG or LPG third
European DSI 2014, Kolding, Denmark
Rankings
Bus Type
A1 Diesel
= wgt
Tcheb
centroid AHP
PROM
TOPSIS
TODIM
10
12
11
11
10
12
12
A2 CNG
8
2-
8
8
9
10
9
A3 LPG
6.5
2
7
7
8
11
8
A4 Hydrogen
11
10
10
10
11
8
10
A5 Methanol
12
9
12
12
12
9
11
A6 Elec OpC
6.5
11
3
3
3
2
6
A7 Elec Dir
2
8
2
2
2
3
2
A8 Elec Bat
1
6
1
1
1
1
1
A9 HybGas
5
2
4
6
7
4
7
A10 HybDies
9
4
9
9
6
7
5
A11 HybCNG
3.5
6
5.5
4.5
4.5
5.5
3.5
A12 HybLPG
3.5
6
5.5
4.5
4.5
5.5
3.5
European DSI 2014, Kolding, Denmark
SELECTION
Bus
Type
Dominance
Simulation
A1
Diesel
A2
CNG
A3
LPG
A4
Hydrogen
Dominated
A5
Methanol
Dominated
A6
Electric optional charge
A7
Electical direct
A8
Electrical battery
0.625
A9
Hybrid gas
0.010
A10
Hybrid diesel
0.045
A11
Hybrid CNG
0.205
A12
Hybrid LPB
A8 picked
A3 picked
A9 picked
0.005
Dominated
0.110
Tchebychef
0
Dominated
All others
Duplicate
European DSI 2014, Kolding, Denmark
Tchebychef
DISCUSSION
• Fair consistency in rankings
• No two identical
• Continuous allows close second to be ranked even if dominated (A7)
• Tchebychef the most extreme
• Only looks at worst
• Thus is sensitive to scale
• A2 considered, though dominated
European DSI 2014, Kolding, Denmark
CONCLUSIONS
• Many multiple criteria methods
• All valuable to some degree
• more
• SIMULATION preferred by author
1. Nondominance might be useful in selection, not in ranking
• You can always come up with another criterion
2. Accuracy of data critical
• A11/A12 identical, but might vary on some additional factor
3. Outranking methods help explore
4. PREFERENCE important
• Machine-methods {omit preference as much as possible} (TOPSIS)
• Individual preference well-studied
• Group preference problematic
European DSI 2014, Kolding, Denmark