Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks
With the escalating global climate change, the cost of carbon emissions has become a crucial metric for evaluating the sustainability of logistics systems. This study addresses the optimisation of cold chain logistics routes in a time-varying network environment, considering the carbon emission cost...
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| Format: | Article |
| Language: | English |
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University of Zagreb, Faculty of Transport and Traffic Sciences
2024-12-01
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| Series: | Promet (Zagreb) |
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| Online Access: | https://traffic2.fpz.hr/index.php/PROMTT/article/view/735 |
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| author | Zeyu WANG Fujian CHEN Chengcheng MO |
| author_facet | Zeyu WANG Fujian CHEN Chengcheng MO |
| author_sort | Zeyu WANG |
| collection | DOAJ |
| description | With the escalating global climate change, the cost of carbon emissions has become a crucial metric for evaluating the sustainability of logistics systems. This study addresses the optimisation of cold chain logistics routes in a time-varying network environment, considering the carbon emission cost factor, and proposes an enhanced particle swarm optimisation algorithm to solve this optimisation problem. Firstly, we establish a cold chain logistics optimisation model that incorporates the time-varying network, integrating logistics route planning with carbon emission costs. Subsequently, we design an improved particle swarm optimisation algorithm suitable for time-varying networks. This algorithm optimises vehicle routes and adjusts delivery times to minimise the total cost incurred during distribution. Finally, through simulation experiments, we analyse the impact of vehicle speeds and carbon trading mechanisms on optimisation outcomes. The results demonstrate that this method effectively optimises cold chain logistics routes, considering real network conditions and environmental factors, thereby reducing delivery costs and carbon emissions. |
| format | Article |
| id | doaj-art-bc50008f9d644e64aaa329a5bc6ae63d |
| institution | OA Journals |
| issn | 0353-5320 1848-4069 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | University of Zagreb, Faculty of Transport and Traffic Sciences |
| record_format | Article |
| series | Promet (Zagreb) |
| spelling | doaj-art-bc50008f9d644e64aaa329a5bc6ae63d2025-08-20T02:34:46ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692024-12-013661103111910.7307/ptt.v36i6.735735Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying NetworksZeyu WANG0Fujian CHEN1Chengcheng MO2Guilin University of Electronic Science and Technology, College of Architecture and Transportation EngineeringGuilin University of Electronic Science and Technology, College of Architecture and Transportation EngineeringGuilin University of Electronic Science and Technology, College of Architecture and Transportation EngineeringWith the escalating global climate change, the cost of carbon emissions has become a crucial metric for evaluating the sustainability of logistics systems. This study addresses the optimisation of cold chain logistics routes in a time-varying network environment, considering the carbon emission cost factor, and proposes an enhanced particle swarm optimisation algorithm to solve this optimisation problem. Firstly, we establish a cold chain logistics optimisation model that incorporates the time-varying network, integrating logistics route planning with carbon emission costs. Subsequently, we design an improved particle swarm optimisation algorithm suitable for time-varying networks. This algorithm optimises vehicle routes and adjusts delivery times to minimise the total cost incurred during distribution. Finally, through simulation experiments, we analyse the impact of vehicle speeds and carbon trading mechanisms on optimisation outcomes. The results demonstrate that this method effectively optimises cold chain logistics routes, considering real network conditions and environmental factors, thereby reducing delivery costs and carbon emissions.https://traffic2.fpz.hr/index.php/PROMTT/article/view/735time-varying networkscarbon emission costscold chain logisticspath optimisationimproved particle swarm algorithm |
| spellingShingle | Zeyu WANG Fujian CHEN Chengcheng MO Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks Promet (Zagreb) time-varying networks carbon emission costs cold chain logistics path optimisation improved particle swarm algorithm |
| title | Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks |
| title_full | Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks |
| title_fullStr | Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks |
| title_full_unstemmed | Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks |
| title_short | Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks |
| title_sort | optimisation methods for cold chain logistics path considering carbon emission costs in time varying networks |
| topic | time-varying networks carbon emission costs cold chain logistics path optimisation improved particle swarm algorithm |
| url | https://traffic2.fpz.hr/index.php/PROMTT/article/view/735 |
| work_keys_str_mv | AT zeyuwang optimisationmethodsforcoldchainlogisticspathconsideringcarbonemissioncostsintimevaryingnetworks AT fujianchen optimisationmethodsforcoldchainlogisticspathconsideringcarbonemissioncostsintimevaryingnetworks AT chengchengmo optimisationmethodsforcoldchainlogisticspathconsideringcarbonemissioncostsintimevaryingnetworks |