Page 414 - Biofuels for a More Sustainable Future

A multicriteria intuitionistic fuzzy group decision-making method 369

3Case study

In order to illustrate the developed multicriteria intuitionistic fuzzy group
decision-making method for sustainability ranking of biofuel production
pathway, three scenarios for bioethanol were investigated by the developed
multicriteria intuitionistic fuzzy group decision-making method, and they
are corn-, wheat-, and cassava-based technologies for bioethanol produc-
tion. The criteria in three categories including economic, environmental,
technological, and social-political aspects were used to rank these three bio-
fuel production pathways. Life cycle cost (LCC) is the only criterion in eco-
nomic aspect to measure economic performance. Four criteria including
climate change (CC), terrestrial acidification (TA), human toxicity (H.
Tox), and particulate matter formation (PMF) were employed to measure
environmental performances. Technology maturity (TM) is used to measure
technology advance. Social benefits (SB), contribution to economic devel-
opment (CED), and food security (FS) were used in social-political category.
Three groups of decision-makers/stakeholders were invited to partici-
pate in the decision-making process, and they are investor group
(DM#1), engineer group (DM#2), and user group (DM#3). The represen-
tative stakeholder in each group was asked to use the linguistic terms pre-
sented in Table 13.2 to rate the three alternative pathways with respect to
each criterion and determine the relative importance of these nine criteria
for sustainability assessment of biofuel production pathways, and the results
are presented in Tables (13.4)–(13.6).
According to Table 13.2, all the linguistic terms presented in
Tables 13.4–13.6 can be transformed into intuitionistic fuzzy numbers,
and the results are presented in Tables 13.7–13.9.
According to Eqs. (13.18), (13.19), the three weighted decision-making
matrices can be determined according to the preferences and opinions of
each group. Taking the data of cell (1,1) in the weighted decision-making
matrix determined by DM#1 as an example:

ð 0:35, 0:55, 0:10Þ
0:95, 0:05, 0Þ
ð
¼ 0:35 0:95, 0:55 + 0:05 0:55 0:05, 1 + 0:55 0:05
ð
ð
0:35 0:95 0:55 0:05Þ¼ 0:3325, 0:5725, 0:0950Þ
In a similar way, all the three weighted decision-making matrices can be
determined. The role importance of the three decision-maker groups
including investor group (DM#1), engineer group (DM#2), and user
group (DM#3) is recognized as very important (VI), important (I), and