Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques

•We model a closed-loop supply chain network with six echelons.•The triple bottom lines of sustainability are modeled as three distinct objectives.•We compare our three proposed algorithms with three benchmark algorithms.•The nested method generates better Pareto-optimal solutions but needs more tim...

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Veröffentlicht in:European journal of operational research Jg. 235; H. 3; S. 594 - 615
Hauptverfasser: Devika, K., Jafarian, A., Nourbakhsh, V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 16.06.2014
Elsevier Sequoia S.A
Schlagworte:
Algorithms
Business
Comparative analysis
Corporate social responsibility
Economics
Environmental impact
Environmental management
Heuristic
Integer programming
Mathematical problems
Metaheuristics
Multi-objective programming
Network design
Networks
Operational research
Studies
Supply chain management
Supply chains
Supply chain management
Corporate social responsibility
Network design
Multi-objective programming
Metaheuristics
Environmental management
ISSN:0377-2217, 1872-6860
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Zusammenfassung:•We model a closed-loop supply chain network with six echelons.•The triple bottom lines of sustainability are modeled as three distinct objectives.•We compare our three proposed algorithms with three benchmark algorithms.•The nested method generates better Pareto-optimal solutions but needs more time. Recently, there is a growing concern about the environmental and social footprint of business operations. While most of the papers in the field of supply chain network design focus on economic performance, recently, some studies have considered environmental dimensions. However, there still exists a gap in quantitatively modeling social impacts together with environmental and economic impacts. In this study, this gap is covered by simultaneously considering the three pillars of sustainability in the network design problem. A mixed integer programming model is developed for this multi-objective closed-loop supply chain network problem. In order to solve this NP-hard problem, three novel hybrid metaheuristic methods are developed which are based on adapted imperialist competitive algorithms and variable neighborhood search. To test the efficiency and effectiveness of these algorithms, they are compared not only with each other but also with other strong algorithms. The results indicate that the nested approach achieves better solutions compared with the others. Finally, a case study for a glass industry is used to demonstrate the applicability of the approach.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2013.12.032