Analysis of planning results for different tu.
<div><p>Road traffic congestion on the cold chain logistics not only increase the cost and time, but also creates certain negative impact on the national carbon emissions. To fully utilize the traffic resources, this study has classified urban road traffic congestion and defined the vari...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| الموضوعات: | |
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| _version_ | 1852023275188649984 |
|---|---|
| author | Wu Kai (20614663) |
| author2 | Lu Zhijiang (20614666) Bai E. (20614669) |
| author2_role | author author |
| author_facet | Wu Kai (20614663) Lu Zhijiang (20614666) Bai E. (20614669) |
| author_role | author |
| dc.creator.none.fl_str_mv | Wu Kai (20614663) Lu Zhijiang (20614666) Bai E. (20614669) |
| dc.date.none.fl_str_mv | 2025-01-24T18:59:53Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0305982.t008 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Analysis_of_planning_results_for_different_tu_/28276069 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biophysics Biotechnology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified scale neighborhood search even vehicle types dynamic congestion levels considering multiple depots cold chain products cold chain logistics algorithm effectively overcomes various replenishment strategies considering delivery route way </ p national carbon emissions efficiently solves multi carbon emissions replenishment along delivery objectives traffic resources sensitivity coefficients objective problems model able fully utilize depot condition computational analysis |
| dc.title.none.fl_str_mv | Analysis of planning results for different tu. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <div><p>Road traffic congestion on the cold chain logistics not only increase the cost and time, but also creates certain negative impact on the national carbon emissions. To fully utilize the traffic resources, this study has classified urban road traffic congestion and defined the various vehicle delivery speeds with dynamic congestion levels. Simultaneously, it has developed the cold chain products replenishment strategy by considering delivery route, multi-depot condition and even vehicle types, aiming to minimize the total cost and carbon emissions, and maximizing the cold chain products freshness. To achieve this, this study build up a multi-objective vehicle routing optimization model and designed a hybrid algorithm combining large-scale neighborhood search and NAGA-II. Through computational analysis, this algorithm effectively overcomes the weak local search capability of NAGA-II and efficiently solves multi-objective problems. Moreover, under the simulated random traffic congestion conditions, this model able to demonstrate relatively stable planning results and address complex road traffic situations. Finally, this study able to analyze the impacts of various replenishment strategies, by considering multiple depots and sensitivity coefficients of cold chain products from delivery objectives. The analysis results also provides valuable insights for actual cold chain logistics distribution industry.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_97d85a4167d2c9e1bdca3f9d719d5e86 |
| identifier_str_mv | 10.1371/journal.pone.0305982.t008 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28276069 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Analysis of planning results for different tu.Wu Kai (20614663)Lu Zhijiang (20614666)Bai E. (20614669)BiophysicsBiotechnologyScience PolicyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedscale neighborhood searcheven vehicle typesdynamic congestion levelsconsidering multiple depotscold chain productscold chain logisticsalgorithm effectively overcomesvarious replenishment strategiesconsidering delivery routeway </ pnational carbon emissionsefficiently solves multicarbon emissionsreplenishment alongdelivery objectivestraffic resourcessensitivity coefficientsobjective problemsmodel ablefully utilizedepot conditioncomputational analysis<div><p>Road traffic congestion on the cold chain logistics not only increase the cost and time, but also creates certain negative impact on the national carbon emissions. To fully utilize the traffic resources, this study has classified urban road traffic congestion and defined the various vehicle delivery speeds with dynamic congestion levels. Simultaneously, it has developed the cold chain products replenishment strategy by considering delivery route, multi-depot condition and even vehicle types, aiming to minimize the total cost and carbon emissions, and maximizing the cold chain products freshness. To achieve this, this study build up a multi-objective vehicle routing optimization model and designed a hybrid algorithm combining large-scale neighborhood search and NAGA-II. Through computational analysis, this algorithm effectively overcomes the weak local search capability of NAGA-II and efficiently solves multi-objective problems. Moreover, under the simulated random traffic congestion conditions, this model able to demonstrate relatively stable planning results and address complex road traffic situations. Finally, this study able to analyze the impacts of various replenishment strategies, by considering multiple depots and sensitivity coefficients of cold chain products from delivery objectives. The analysis results also provides valuable insights for actual cold chain logistics distribution industry.</p></div>2025-01-24T18:59:53ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0305982.t008https://figshare.com/articles/dataset/Analysis_of_planning_results_for_different_tu_/28276069CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/282760692025-01-24T18:59:53Z |
| spellingShingle | Analysis of planning results for different tu. Wu Kai (20614663) Biophysics Biotechnology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified scale neighborhood search even vehicle types dynamic congestion levels considering multiple depots cold chain products cold chain logistics algorithm effectively overcomes various replenishment strategies considering delivery route way </ p national carbon emissions efficiently solves multi carbon emissions replenishment along delivery objectives traffic resources sensitivity coefficients objective problems model able fully utilize depot condition computational analysis |
| status_str | publishedVersion |
| title | Analysis of planning results for different tu. |
| title_full | Analysis of planning results for different tu. |
| title_fullStr | Analysis of planning results for different tu. |
| title_full_unstemmed | Analysis of planning results for different tu. |
| title_short | Analysis of planning results for different tu. |
| title_sort | Analysis of planning results for different tu. |
| topic | Biophysics Biotechnology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified scale neighborhood search even vehicle types dynamic congestion levels considering multiple depots cold chain products cold chain logistics algorithm effectively overcomes various replenishment strategies considering delivery route way </ p national carbon emissions efficiently solves multi carbon emissions replenishment along delivery objectives traffic resources sensitivity coefficients objective problems model able fully utilize depot condition computational analysis |