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SUSTAINABILITY MCDM MODEL COMPARISONS. Yuan-Sheng Lee, Tamkang University Hsu-Shih Shih, Tamkang University David L. Olson, University of Nebraska. SUSTAINABILITY Tzeng et al. [2005] Energy Policy. DECISION: select bus type from 12 choices Eleven criteria Our use:

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sustainability mcdm model comparisons

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
SUSTAINABILITYTzeng 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
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
Urban Transportation Selection DecisionSelect 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

todim
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

part 1
Part 1:

European DSI 2014, Kolding, Denmark

part ii
Part II

European DSI 2014, Kolding, Denmark

non dominance
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

weighting
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
Simulation

European DSI 2014, Kolding, Denmark

promethee
PROMETHEE

European DSI 2014, Kolding, Denmark

distance methods
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
Rankings

European DSI 2014, Kolding, Denmark

selection
SELECTION

European DSI 2014, Kolding, Denmark

discussion
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
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

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