Page 182 - Materials Chemistry, Second Edition

180 9. Life cycle decision support framework: Method and case study

9.2.4 Aggregation
Aggregation is the final step of MCDM to determine the rank or the selection result of the
decision-making problem. In this step, a model is applied to integrate the criteria data with
criteria weights to generate a clear result of priority of alternatives. To study the development
trend of aggregation methods used in studies combining MCDM and LSCA, the ranking or
aggregating methods are summarized in Table 9.2.
From Table 9.2, the technique for order preference by similarity to an ideal solution
(TOPSIS) method (Yoon and Hwang, 1995) and its interval version are the most acceptable
and popularly used in the case studies. Similar to the development of weighting methods,
some studies have extended MCDM to be applied in interval number, fuzzy number, rough
number, and other types of number to take uncertainties into consideration.

TABLE 9.2 Aggregating methods used in sustainability assessment.

Method Reference
Crisp number
WSM/SMART/SAW Castillo and Pitfield (2010), Jeon et al. (2010), Simonga ´ti (2010), Akadiri et al. (2013),
Palevi cius et al. (2013), Akhtar et al. (2015), Klein and Whalley (2015), Marzouk and
Elmesteckawi (2015), Ozcan-Deniz and Zhu (2015), Mitropoulos and Prevedouros
(2016), Osorio-Tejada et al. (2017), Rashidi et al. (2017), Ren et al. (2017a), Opher et al.
(2018b), Roinioti and Koroneos (2019)
ˇ
TOPSIS Palevi cius et al. (2013), Sioz ˇinyt_ e et al. (2014), Validi et al. (2014), Formisano and
Mazzolani (2015), Terracciano et al. (2015), Govindan et al. (2016), Balez ˇentis and
ˇ
Streimikiene (2017), Gao et al. (2017), Rashid et al. (2017), Ren et al. (2017a), Skobalj et al.
(2017), Jia et al. (2018), Tahmasebi Birgani and Yazdandoost (2018), Tang et al. (2018),
Yazdani et al. (2018)
ˇ
GRA Manzardo et al. (2012), Sioz ˇinyt_ e et al. (2014), Zhao and Li (2016)
VIKOR Vu cijak et al. (2013), Hsu et al. (2014), Formisano and Mazzolani (2015), Kuo et al. (2015),
Ren et al. (2015), Zhao and Li (2016), B€ uy€ uk€ ozkan and Karabulut (2017), Luthra et al.
(2017a), Huang et al. (2018), Zheng et al. (2019)
ELECTRE I/IV/IS/II/ Bojkovi c et al. (2010), Khalili and Duecker (2013), Barata et al. (2014), Formisano and
III/IV/TRI Mazzolani (2015)
PROMETHEE I/II Safaei Mohamadabadi et al. (2009), Tsoutsos et al. (2009), Simonga ´ti (2010), Hayashi et al.
(2016), Ren et al. (2016), Gao et al. (2017), Alhumaid et al. (2018), Mahbub et al. (2018),
Zhang et al. (2018)
WASPAS Zhang et al. (2015), Balez ˇentis and Streimikiene (2017)
COPRAS Palevi cius et al. (2013), Zhang et al. (2015), B€ uy€ uk€ ozkan and Karabulut (2017)
ARAS Balez ˇentis and Streimikiene (2017)
MABAC Debnath et al. (2017), Wang et al. (2019)
MAIRCA Pamucar et al. (2018)
MIVES San-Jos e Lombera and Cuadrado Rojo (2010), Del Can ˜o et al. (2012), Pons and De La
Fuente (2013), Amin Hosseini et al. (2016), De La Fuente et al. (2016), Pujadas et al. (2017)