Page 361 - Biofuels for a More Sustainable Future

318 Biofuels for a More Sustainable Future

contribute to the society to some extent under suitable situation. Job crea-
tion through the central policy of biofuel also could make a difference
toward the development of the economy and society (Demirbas, 2009).
Accordingly, different pathways for biofuel production have different
sustainability performances, and developing a method for helping the
stakeholders/decision-makers to select the most sustainable pathway for
biofuel production is of vital importance.
The selection of the most sustainable pathway for biofuel production
usually involves a set of criteria in multiple aspects including economic,
environmental, technological, and social-political aspects, thus, it is usually
a multicriteria decision making (MCDM) problem. Multicriteria decision
making methods aim at ranking a set of alternatives with the considerations
of multiple criteria, and the combination of sustainability assessment and
MCDM method can achieve sustainability ranking of alternatives
(An et al., 2016). Scott et al. (2012) revealed that the most popular applica-
tion of MCDM methods used in the area of bioenergy is technology selec-
tion. Perimenis et al. (2011) developed a multicriteria analysis method as the
decision support tool for the assessment of biofuels with the considerations
of economic, environmental, and social aspects along the biofuel production
chain. Cobuloglu and B€uy€uktahtakın (2015) developed a stochastic analytic
hierarchy process (AHP) method for the selection of sustainable biomass
crop for biofuel production by considering economic, environmental,
and social dimensions.
Uncertainty, which results from language description and probability
and statics, generally exists in practical problems. Fuzzy set theory was thus
introduced to MCDM field named Fuzzy Multiple Criteria Decision Mak-
ing (FMCDM), aiming at handing the problems with linguistic variables
properly. Previous studies have shown the feasibility of the application of
FMCDM in various fields, including engineering, technology, science,
management, and economy (Mardani et al., 2015; Behzadian et al.,
2010). MCDM and fuzzy MCDM have been divided into many domains
and methods by a group of researchers (Mardani et al., 2015; Balez ˇentis
et al., 2010; Liou, 2013). Generally speaking, fuzzy MCDM methods can
be classified as fuzzy multiobjective decision making (DMODM) accesses
and fuzzy multiattribute decision making (FMADM) approaches
(Mardani et al., 2015; Kadane, 2011; Liou and Tzeng, 2012). Actually, there
exist various classifications of FMCDM tools based on different principles.
For instance, Peneva and Popchev (2008) pointed out that the problems
with real numbers as weight, the methods, like Weighted Mean