A fuzzy robust optimization model for dual objective forward and reverse logistics networks considering carbon emissions.
The inherent unpredictability within the low-carbon integrated supply chain logistics network complicates its management. This paper endeavours to address the challenge of designing a low-carbon logistics network within a context of uncertainty and with consideration of low-carbon policies. It also...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316197 |
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| Summary: | The inherent unpredictability within the low-carbon integrated supply chain logistics network complicates its management. This paper endeavours to address the challenge of designing a low-carbon logistics network within a context of uncertainty and with consideration of low-carbon policies. It also endeavours to identify locations of facilities and appropriate transportation routes between nodes. Robust optimisation and fuzzy programming techniques are employed to examine the various attributes of the network. In addition, the strategic planning model of a multi-level forward/reverse integration logistics network is examined, with the aims of cost minimisation and emission reduction. Extensive computational simulations substantiate the efficacy of the proposed robust fuzzy programming model. Moreover, analytical results indicate the rationality and applicability of the decisions suggested by the proposed optimisation model and the solution approach. Furthermore, the results indicate that a decision maker can ascertain that the decisions derived from three cases considered have a 50% probability of being the most favourable outcomes. |
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| ISSN: | 1932-6203 |