Novel robust fuzzy programming for closed-loop supply chain network design under hybrid uncertainty
In this paper, a mixed-integer nonlinear programming model is developed for a general edible oil closed loop supply chain network design problem under hybrid uncertainty which is then transformed to its linear counterpart. In order to cope with the hybrid uncertainty in input parameters, scenario-ba...
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| Veröffentlicht in: | Journal of intelligent & fuzzy systems 2019-01, Vol.37 (5), p.6457-6470 |
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| container_end_page | 6470 |
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| container_issue | 5 |
| container_start_page | 6457 |
| container_title | Journal of intelligent & fuzzy systems |
| container_volume | 37 |
| creator | Dehghan, Ehsan Amiri, Maghsoud Shafiei Nikabadi, Mohsen Jabbarzadeh, Armin |
| description | In this paper, a mixed-integer nonlinear programming model is developed for a general edible oil closed loop supply chain network design problem under hybrid uncertainty which is then transformed to its linear counterpart. In order to cope with the hybrid uncertainty in input parameters, scenario-based and fuzzy- based parameters, a new approach is proposed including a novel robust fuzzy programming and an efficient method based on the Me measure. Furthermore, the performance of the proposed model is compared with that of other models. Finally, numerical studies and simulation are performed to verify our mathematical formulation and demonstrate the benefits of the proposed model. |
| doi_str_mv | 10.3233/JIFS-18117 |
| format | Article |
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| language | eng |
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| source | EBSCOhost Business Source Complete |
| subjects | Closed loops Computer simulation Mathematical models Network design Nonlinear programming Parameter uncertainty Robustness (mathematics) Supply chains |
| title | Novel robust fuzzy programming for closed-loop supply chain network design under hybrid uncertainty |
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