Developing a bi-objective model of the closed-loop supply chain network with green supplier selection and disassembly of products: The impact of parts reliability and product greenness on the recovery network

Multi-criteria decision making approaches for green supply chains: a review

“…These findings show that gaps in literature exists concerning the use of MCDM approaches to support inventory management decisions with respect to economic and environmental criteria. Reverse logistics is considered in 27 publications, while only 11 papers combined forward and reverse logistics to support decision making in a closed-loop supply chain (Govindan et al 2016a;Garg et al 2015;Ghayebloo et al 2015;Mota et al 2015;Devika et al 2014;Kannegiesser and Gunther 2014;Oh and Jeong 2014;Pishvaee et al 2014;Ozkir and Basligil 2013;Paksoy et al 2012;Quariguasi Frota Neto et al 2010). Only few of the papers dealing with modelling material flows in a closed-loop supply chain presents a case study with realistic data.…”

“…However, such newly created measures continue to emerge (e.g. environmental impact score in Inghels et al (2016), greenness level in Ghayebloo et al (2015)), indicating the lack of standards.…”

“…Among non-deterministic models fuzzy set theory is most frequently applied to take uncertainty into account. Fuzzy set theory is used to take et al (2015), Gao and You (2015), Garcia and You (2015b), Garg et al (2015), Ghayebloo et al (2015), Kostin et al (2015), Mota et al (2015), Nagurney (2015), SantibanezAguilar et al (2015), Shimizu et al (2015), Tognetti et al (2015), Yu et al (2015), Yue et al (2015), Devika et al (2014), Govindan et al (2014a) 59 (38) 110 (19) 19 (8) 188 (65) a Publication with non-deterministic parameter(s)…”

Literature Review

“…The relative importance of the globalization aspects has decreased while the number of papers devoted to environmental aspects and reverse (5) Altmann (2014), Brandenburg (2015), Cui (2015), Klibi and Martel (2012) Note: The number of papers for each specific problem is given in parenthesis. See key from Table 3.1 for abbreviations 3.4 Focus Areas for Supply Chain Configuration (7) Brandenburg (2015), Castellano et al (2013), Petridis (2015), Tian and Yue (2014), Tiacci et al (2014), You and Grossmann (2008), Zokaee et al (2014) ENV (9) Altmann ( (7) Baghalian et al (2013), Bassett and Gardner (2013), Habermann et al (2015), Hearnshaw and Wilson (2013), Klibi and Martel (2012), Madadi et al (2014), Mizgier et al (2015) RL (12) Amin and Zhang (2012), Chaabane et al (2012), Das and Rao Posinasetti (2015), Ghayebloo et al (2015), Kara and Onut (2010), Metta andBadurdeen (2013), Quariguasi Frota Neto et al (2008), Ramezani et al (2013), Ramezani et al (2014), Santibanez-Gonzalez and, Soleimani et al (2013), Vahdani and Naderi-Beni (2014) RP (6) Akanle and Zhang (2008), Bottani andMontanari (2010), Cheung et al (2012), Jamshidi et al (2015), Vanteddu et al (2011), You and…”

A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: Considering collection and recycling centers

“…What is more, recently, researchers have shown an increased interest in GSCM models to reduce serious environmental implications associated with differing supply chain activities (see e.g. [1][2][3][4][5][6][7][8][9][10]). At the same time, with regard to manufacturing, 'green distribution, green logistics, green marketing' and 'reverse logistics' [17].…”