Design of sustainable supply chains under the emission trading scheme
By Amin Chaabane, Amar Ramudhin, Marc Paquet. 2012
849 citations recorded by the source corpus.
Subfields: Environmental Engineering, Industrial and Manufacturing Engineering, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/4d523054e2d0ee9b29ba912446e0e5836bc038f4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Behnam Fahimnia
- Joseph Sarkis
- Armin Jabbarzadeh
- Lynn H. Kaack
- Kannan Govindan
- Yoshua Bengio
- Jacqueline M. Bloemhof
- Farzad Dehghanian
In Industrial and Manufacturing Engineering
- Kannan Govindan
- Mehmet Soysal
- Behnam Fahimnia
- Joseph Sarkis
- Devika Kannan
- Lynn H. Kaack
- Angappa Gunasekaran
- Rommert Dekker
In Strategy and Management
- Kannan Govindan
- Behnam Fahimnia
- Fatemeh Sabouhi
- Armin Jabbarzadeh
- Mehmet Soysal
- Angappa Gunasekaran
- Joseph Sarkis
- Devika Kannan
Citations in the corpus
- A Review on Quantitative Models for Sustainable Food Logistics Management (2012, background): “(Bettley and Burnley, 2008b) (Chaabane et al., 2012) (Dekker et al.”
- Multi-item production planning with carbon cap and trade mechanism (2013, background): “Many research on green supply chain investigated closed-loop supply chain or sustainable usage of material, such as Srivastava (2007), Chaabane et al. (2012) and Shi et al. (2011).”
- Operations Research for green logistics - An overview of aspects, issues, contributions and challenges (2011, background): “Chaabane et al. (2012) extend this approach and introduce a mixed-integer linear programming based framework for sustainable supply chain design that considers life cycle assessment (LCA) principles in addition to the traditional material balance constraints at each node in the supply chain.”
- Tactical supply chain planning under a carbon tax policy scheme: A case study (2015, background): “Mixed-integer linear programming (MILP) frameworks have been popular for addressing sustainable SC design issues with material balance constraints from traditional operations and SC topics, to new technology introduction modeling (Chaabane et al., 2012).”