A multi-objective optimization for green supply chain network design
By Fan Wang, Xiaofan Lai, Ning Shi. Decision Support Systems, 2011
677 citations recorded by the source corpus.
Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/8e8f5c5d1e6aaf61c4b8c3e922b8cc4fd3a20227
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
- Kannan Govindan
- Armin Jabbarzadeh
- Behnam Fahimnia
- Fatemeh Sabouhi
- K. P. Nurjanni
- Jacqueline Bloemhof-Ruwaard
- Pierre J. Dejax
- Jack G. A. J. van der Vorst
In Management Science and Operations Research
- Kannan Govindan
- Behnam Fahimnia
- Ali Eshragh
- Alok Kumar Choudhary
- Stefan Seuring
- Roohollah Khodaverdi
- Sahar Validi
- Joseph Sarkis
In Strategy and Management
- Behnam Fahimnia
- Kannan Govindan
- Joseph Sarkis
- Armin Jabbarzadeh
- Fatemeh Sabouhi
- Mehmet Soysal
- Devika Kannan
- Stefan Seuring
Citations in the corpus
- Robust possibilistic programming for socially responsible supply chain network design: A new approach (2012, neutral): “, [15,16]).”
- A case analysis of a sustainable food supply chain distribution system—A multi-objective approach (2014, background): “Trade-offs between cost factors and environmental impact of a supply chain is reported in Wang et al. (2011).”
- Sustainable supply chain network design: An optimization-oriented review☆ (2015, methodology): “The overall justification of research in this area can be summarized by the observation that the consideration of sustainable development factors may have a significant impact on the design and configuration of the supply chain, as illustrated by the case study in You and Wang [2011]. Amidst the man”
- Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future (2015, background): “Chung and Wee (2008), Qiaolun, Jianhua, and Tiegang (2008), Wang, Lai, and Shi (2011), and Sun, Wu, and Hu (2013) serve as suggested papers here.”
- Green supply chain design: a mathematical modeling approach based on a multi-objective optimization model (2017, background): “Furthermore, there is a few number of approaches combining financial and environmental issues explicitly in OL multi-objective frameworks to address the supply chain design problem: Wang et al. (2011), Jamshidi et al. (2012), Pozo et al. (2012), Sabio et al. (2012), and Giarola et al. (2011).”
- Operations Research for green logistics - An overview of aspects, issues, contributions and challenges (2011, background): “Wang et al. (2011) suggest a multi-objective optimization model for supply chain network design.”
- A Bibliometric Analysis of Green Supply Chain Management Based on the Web of Science (WOS) Platform (2019, neutral): “(2011) A multi-objective optimization for green supply chain network design [43].”
- Tactical supply chain planning under a carbon tax policy scheme: A case study (2015, positive): “Some recent GSCM modeling efforts have focused on designing networks with emissions and life-cycle analysis considerations (Bojarski et al., 2009; Diabat et al., 2013; Wang et al., 2011).”
- Quantitative models for sustainable supply chain management: Developments and directions (2014, background): “, 2011) or to consider transportation modes or demand uncertainties (Wang et al., 2011).”
- Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food (2014, background): “, 2011), papers that specifically address environmental and social objects in the design stage are limited (Wang et al., 2011).”
- Modelling food logistics networks with emission considerations: The case of an international beef supply chain (2014, background): “First approach, which is preferred most, is using fixed emission or environmental impact factors per distance unit and/or per weight unit (e.g. Chaabane et al., 2008; Wang et al., 2011), per product (e.g.”