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Prioritization of biofuels production pathways under uncertainties  353


                    8
                   7.5
                    7
                   6.5
                    6
                                                                Wheat-based
                   5.5
                                                                Corn-based
                    5                                           Cassava-based
                   4.5
                    4
                   3.5
                    3
                     Case 0 Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 Case 8
              Fig. 12.2 The results of sensitivity analysis.



                 The results of sensitivity analysis are presented in Fig. 12.2. It is apparent
              that the results are robust; the sustainability sequence from the most sustain-
              able to the least is corn-, cassava-, and wheat-based pathways for bioethanol
              production in all the nine cases.



              5 Conclusion

              This study developed an interval multicriteria decision making method for
              sustainability ranking of alternative biofuel production pathways, the inter-
              val AHP was employed to determine the weights (relative importance) of
              the criteria for sustainability assessment of biofuel production pathways,
              and the interval GRA method was employed to determine the sustainabil-
              ity sequence of the alternative biofuel production pathways. The devel-
              oped interval multicriteria decision making method for sustainability
              ranking of alternative biofuel production pathways has the following
              two advantages:
              (1) The use of interval AHP method can effectively address the ambiguity,
                 hesitation, and vagueness existing in human’s judgments when compar-
                 ing the relative preference of a criterion over another.
              (2) The use of interval GRA can achieve multicriteria decision making
                 under uncertainties, because the data in the decision-making matrix
                 are interval numbers rather than the traditional crisp numbers.
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