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SUSTAINABILITY MCDM MODEL COMPARISONS Yuan-Sheng Lee, Tamkang University Hsu-Shih Shih, Tamkang University David L. Olson, University of Nebraska European.

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Presentation on theme: "SUSTAINABILITY MCDM MODEL COMPARISONS Yuan-Sheng Lee, Tamkang University Hsu-Shih Shih, Tamkang University David L. Olson, University of Nebraska European."— Presentation transcript:

1 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

2 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

3 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

4 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

5 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

6 Part 1: Bus TypeEnergy Supply Energy Efficiency Air PollutionNoise Pollution Industrial Relations Employ Cost A1 Diesel A2 CNG A3 LPG A4 Hydrogen A5 Methanol A6 Elec OpC A7 Elec Dir !8 Elec Bat A9 HybGas A10 HybDies A11 HybCNG A12 HybLPG European DSI 2014, Kolding, Denmark

7 Part II Bus TypeMaintenance cost Vehicle capability RoadsTraffic speedComfort A1 Diesel A2 CNG A3 LPG A4 Hydrogen A5 Methanol A6 Elec OpC A7 Elec Dir A8 Elec Bat A9 HybGas A10 HybDies A11 HybCNG A12 HybLPG European DSI 2014, Kolding, Denmark

8 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

9 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

10 Simulation Bus Type (nondominated)Proportion Won A1Diesel0.005 A3LPG0.110 A6Electric optional charging0 A8Electric battery0.625 A9Hybrid gas0.110 A10Hybrid diesel0.045 A11Hybrid CNG or LPG0.205 European DSI 2014, Kolding, Denmark

11 PROMETHEE European DSI 2014, Kolding, Denmark

12 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

13 Rankings Bus Type= wgtTchebcentroidAHPPROMTOPSISTODIM A1 Diesel A2 CNG A3 LPG A4 Hydrogen A5 Methanol A6 Elec OpC A7 Elec Dir A8 Elec Bat A9 HybGas A10 HybDies A11 HybCNG A12 HybLPG European DSI 2014, Kolding, Denmark

14 SELECTION Bus Type DominanceSimulationA8 pickedA3 pickedA9 picked A1Diesel0.005 A2CNGDominated A3LPG0.110Tchebychef A4HydrogenDominated A5MethanolDominated A6Electric optional charge0 A7Electical directDominated A8Electrical battery0.625All others A9Hybrid gas0.010Tchebychef A10Hybrid diesel0.045 A11Hybrid CNG0.205 A12Hybrid LPBDuplicate European DSI 2014, Kolding, Denmark

15 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

16 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


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