Solving a low-carbon routing problem for perishable distribution food
This research article presents a low-carbon and environmental protection viewpoint that combines the idea of a cold chain. In this case, the optimisation problem Food distribution system is solved by developing a low-carbon Routing Problem (LRP) model. The researchers seek to identify the minimum co...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | International Journal of Sustainable Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19397038.2024.2409157 |
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| _version_ | 1846126776635359232 |
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| author | Martinson Yeboah Appiah Sun Huaping |
| author_facet | Martinson Yeboah Appiah Sun Huaping |
| author_sort | Martinson Yeboah Appiah |
| collection | DOAJ |
| description | This research article presents a low-carbon and environmental protection viewpoint that combines the idea of a cold chain. In this case, the optimisation problem Food distribution system is solved by developing a low-carbon Routing Problem (LRP) model. The researchers seek to identify the minimum costs and carbon emission costs while Carbon tax policies are also presented to examine their effects on carbon emissions. The model is solved by using a hybrid genetic algorithm with heuristic rules, after which the algorithm’s efficiency is tested with a globally recognised Proudhon data set. The Cycle evolutionary algorithm can quickly and effectively seek the optimal solution of the model. We combine two kinds of operators, inversion mutation and insertion mutation, in the genetic algorithm to form the combined operator of a hybrid genetic algorithm. Then, the approximate optimal solution is obtained. Meanwhile, many experiments are carried out by setting different carbon tax values and the critical interval values of carbon emissions and optimal. A case study from a third-party logistics company is used to test the applicability of the model in the real world. Results showed that the model and carbon tax policies will benefit business operations and the environment. |
| format | Article |
| id | doaj-art-2332df9fdc8344fca5700b5f9d2c123b |
| institution | Kabale University |
| issn | 1939-7038 1939-7046 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Engineering |
| spelling | doaj-art-2332df9fdc8344fca5700b5f9d2c123b2024-12-12T09:30:53ZengTaylor & Francis GroupInternational Journal of Sustainable Engineering1939-70381939-70462024-12-0117186788210.1080/19397038.2024.2409157Solving a low-carbon routing problem for perishable distribution foodMartinson Yeboah Appiah0Sun Huaping1School of Finance and Economics, Jiangsu University, Zhenjiang, ChinaSchool of Finance and Economics, Jiangsu University, Zhenjiang, ChinaThis research article presents a low-carbon and environmental protection viewpoint that combines the idea of a cold chain. In this case, the optimisation problem Food distribution system is solved by developing a low-carbon Routing Problem (LRP) model. The researchers seek to identify the minimum costs and carbon emission costs while Carbon tax policies are also presented to examine their effects on carbon emissions. The model is solved by using a hybrid genetic algorithm with heuristic rules, after which the algorithm’s efficiency is tested with a globally recognised Proudhon data set. The Cycle evolutionary algorithm can quickly and effectively seek the optimal solution of the model. We combine two kinds of operators, inversion mutation and insertion mutation, in the genetic algorithm to form the combined operator of a hybrid genetic algorithm. Then, the approximate optimal solution is obtained. Meanwhile, many experiments are carried out by setting different carbon tax values and the critical interval values of carbon emissions and optimal. A case study from a third-party logistics company is used to test the applicability of the model in the real world. Results showed that the model and carbon tax policies will benefit business operations and the environment.https://www.tandfonline.com/doi/10.1080/19397038.2024.2409157Logistics distributionlocation-routing problemgenetic algorithmcycle evolutionary algorithmvehicle routing problem |
| spellingShingle | Martinson Yeboah Appiah Sun Huaping Solving a low-carbon routing problem for perishable distribution food International Journal of Sustainable Engineering Logistics distribution location-routing problem genetic algorithm cycle evolutionary algorithm vehicle routing problem |
| title | Solving a low-carbon routing problem for perishable distribution food |
| title_full | Solving a low-carbon routing problem for perishable distribution food |
| title_fullStr | Solving a low-carbon routing problem for perishable distribution food |
| title_full_unstemmed | Solving a low-carbon routing problem for perishable distribution food |
| title_short | Solving a low-carbon routing problem for perishable distribution food |
| title_sort | solving a low carbon routing problem for perishable distribution food |
| topic | Logistics distribution location-routing problem genetic algorithm cycle evolutionary algorithm vehicle routing problem |
| url | https://www.tandfonline.com/doi/10.1080/19397038.2024.2409157 |
| work_keys_str_mv | AT martinsonyeboahappiah solvingalowcarbonroutingproblemforperishabledistributionfood AT sunhuaping solvingalowcarbonroutingproblemforperishabledistributionfood |