Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels
The ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In t...
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MDPI AG
2021-04-01
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| Series: | Logistics |
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| Online Access: | https://www.mdpi.com/2305-6290/5/2/20 |
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| author | Mohsen Tehrani Surendra M. Gupta |
| author_facet | Mohsen Tehrani Surendra M. Gupta |
| author_sort | Mohsen Tehrani |
| collection | DOAJ |
| description | The ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In the real world, the CLSC network design is subject to a variety of uncertainties, such as random and fuzzy (epistemic) uncertainties. Designing a reliable and environmentally cautious CLSC with consideration of risks and the uncertainty of the parameters in the network is necessary for a successful supply-chain network. This study proposes a sustainable and environmentally cautious closed-loop supply-chain network for the tire industry, by considering several recovery options, including retreading, recycling, and energy recovery. This study aims to design and develop a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty. There are two types of uncertainties associated with the parameters in the network. There is an uncertainty associated with the demand, which is expressed in some future scenarios according to the probability of their occurrences, as well as fuzzy-based uncertainty associated with return rates, retreading rates, recycling rates, procurement, and production costs, which are expressed with possibilistic distributions. In order to deal with this hybrid uncertainty, a robust fuzzy stochastic programming approach has been proposed, and the proposed mixed integer programming model is applied to a case study in the tire industry to validate the model. The result indicates the applicability of the proposed model and its efficiency to control the hybrid uncertainties and the risk level in the network. |
| format | Article |
| id | doaj-art-3f070c0eea094869923faaaac7cac280 |
| institution | DOAJ |
| issn | 2305-6290 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Logistics |
| spelling | doaj-art-3f070c0eea094869923faaaac7cac2802025-08-20T03:15:43ZengMDPI AGLogistics2305-62902021-04-01522010.3390/logistics5020020Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity LevelsMohsen Tehrani0Surendra M. Gupta1Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USADepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USAThe ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In the real world, the CLSC network design is subject to a variety of uncertainties, such as random and fuzzy (epistemic) uncertainties. Designing a reliable and environmentally cautious CLSC with consideration of risks and the uncertainty of the parameters in the network is necessary for a successful supply-chain network. This study proposes a sustainable and environmentally cautious closed-loop supply-chain network for the tire industry, by considering several recovery options, including retreading, recycling, and energy recovery. This study aims to design and develop a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty. There are two types of uncertainties associated with the parameters in the network. There is an uncertainty associated with the demand, which is expressed in some future scenarios according to the probability of their occurrences, as well as fuzzy-based uncertainty associated with return rates, retreading rates, recycling rates, procurement, and production costs, which are expressed with possibilistic distributions. In order to deal with this hybrid uncertainty, a robust fuzzy stochastic programming approach has been proposed, and the proposed mixed integer programming model is applied to a case study in the tire industry to validate the model. The result indicates the applicability of the proposed model and its efficiency to control the hybrid uncertainties and the risk level in the network.https://www.mdpi.com/2305-6290/5/2/20closed-loop supply chainlocation–allocation problemrobust optimizationtire industrymulti-objective decision makinghybrid uncertainty |
| spellingShingle | Mohsen Tehrani Surendra M. Gupta Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels Logistics closed-loop supply chain location–allocation problem robust optimization tire industry multi-objective decision making hybrid uncertainty |
| title | Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels |
| title_full | Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels |
| title_fullStr | Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels |
| title_full_unstemmed | Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels |
| title_short | Designing a Sustainable Green Closed-Loop Supply Chain under Uncertainty and Various Capacity Levels |
| title_sort | designing a sustainable green closed loop supply chain under uncertainty and various capacity levels |
| topic | closed-loop supply chain location–allocation problem robust optimization tire industry multi-objective decision making hybrid uncertainty |
| url | https://www.mdpi.com/2305-6290/5/2/20 |
| work_keys_str_mv | AT mohsentehrani designingasustainablegreenclosedloopsupplychainunderuncertaintyandvariouscapacitylevels AT surendramgupta designingasustainablegreenclosedloopsupplychainunderuncertaintyandvariouscapacitylevels |