# SUSTAINABILITY MCDM MODEL COMPARISONS

## Presentation on theme: "SUSTAINABILITY MCDM MODEL COMPARISONS"— Presentation transcript:

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

European DSI 2014, Kolding, Denmark
Urban Transportation Selection Decision Select a bus type – CRITERIA (Tzeng et al., 2005) 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

European DSI 2014, Kolding, Denmark
TODIM Classify multiple criteria into benefits, costs 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

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 0.52 A3 LPG 0.79 A4 Hydrogen 0.63 0.86 0.51 A5 Methanol 0.40 0.54 0.69 A6 Elec OpC 0.76 0.89 0.60 0.72 0.80 A7 Elec Dir !8 Elec Bat A9 HybGas 0.66 A10 HybDies A11 HybCNG 0.48 A12 HybLPG European DSI 2014, Kolding, Denmark

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 A4 Hydrogen 0.74 0.63 0.70 A5 Methanol 0.68 0.52 0.60 A6 Elec OpC 0.72 0.54 0.35 A7 Elec Dir 0.47 0.44 0.87 0.75 A8 Elec Bat 0.51 0.48 A9 HybGas 0.65 0.80 A10 HybDies A11 HybCNG 0.71 0.62 A12 HybLPG European DSI 2014, Kolding, Denmark

European DSI 2014, Kolding, Denmark
NON-DOMINANCE 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

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) CARDINAL WEIGHTS (from Tzeng et al. - AHP) European DSI 2014, Kolding, Denmark

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 A10 Hybrid diesel 0.045 A11 Hybrid CNG or LPG 0.205 European DSI 2014, Kolding, Denmark

European DSI 2014, Kolding, Denmark
PROMETHEE European DSI 2014, Kolding, Denmark

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 A7 Electric direct exchange (dominated solution) second A11/A12 Hybrid CNG or LPG third European DSI 2014, Kolding, Denmark

European DSI 2014, Kolding, Denmark
Rankings Bus Type = wgt Tcheb centroid AHP PROM TOPSIS TODIM A1 Diesel 10 12 11 A2 CNG 8 2- 9 A3 LPG 6.5 2 7 A4 Hydrogen A5 Methanol A6 Elec OpC 3 6 A7 Elec Dir A8 Elec Bat 1 A9 HybGas 5 4 A10 HybDies A11 HybCNG 3.5 5.5 4.5 A12 HybLPG European DSI 2014, Kolding, Denmark

European DSI 2014, Kolding, Denmark
SELECTION Bus Type Dominance Simulation A8 picked A3 picked A9 picked A1 Diesel 0.005 A2 CNG Dominated A3 LPG 0.110 Tchebychef A4 Hydrogen A5 Methanol A6 Electric optional charge A7 Electical direct A8 Electrical battery 0.625 All others A9 Hybrid gas 0.010 A10 Hybrid diesel 0.045 A11 Hybrid CNG 0.205 A12 Hybrid LPB Duplicate European DSI 2014, Kolding, Denmark

European DSI 2014, Kolding, Denmark
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

European DSI 2014, Kolding, Denmark
CONCLUSIONS Many multiple criteria methods All valuable to some degree more SIMULATION preferred by author Nondominance might be useful in selection, not in ranking You can always come up with another criterion Accuracy of data critical A11/A12 identical, but might vary on some additional factor Outranking methods help explore PREFERENCE important Machine-methods {omit preference as much as possible} (TOPSIS) Individual preference well-studied Group preference problematic European DSI 2014, Kolding, Denmark