Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption
Abstract With the increasing demand for fresh food markets, refrigerated transportation has become an essential component of logistics operations. Currently, fresh food transportation frequently faces issues of high energy consumption and high costs, which are inconsistent with the development needs...
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-78639-1 |
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| author | Hao Chen Wenxian Wang Li Jia Haiming Wang |
| author_facet | Hao Chen Wenxian Wang Li Jia Haiming Wang |
| author_sort | Hao Chen |
| collection | DOAJ |
| description | Abstract With the increasing demand for fresh food markets, refrigerated transportation has become an essential component of logistics operations. Currently, fresh food transportation frequently faces issues of high energy consumption and high costs, which are inconsistent with the development needs of the modern logistics industry. This paper addresses the optimization problem of multi-vehicle type fresh food distribution under time-varying conditions. It comprehensively considers the changes in road congestion at different times and the quality degradation characteristics of fresh goods during distribution. The objectives include transportation cost, dual carbon cost, and damage cost, subject to constraints such as delivery time windows and vehicle capacity. A piecewise function is used to depict vehicle speeds, proposing a dynamic urban fresh food logistics vehicle routing optimization method. Given the NP-hard nature of the problem, a hybrid Tabu Search (TS) and Genetic Algorithm (GA) approach is designed to compute an optimal solution. Comparison with TS and GA algorithm results shows that the TS-GA algorithm provides the best optimization efficiency and effectiveness for solving large-scale distribution problems. The results indicate that using the TS-GA algorithm to optimize a distribution network with one distribution center and 30 delivery points resulted in a total cost of CNY 12,934.02 and a convergence time of 16.3 s. For problems involving multiple vehicle types and multiple delivery points, the TS-GA algorithm reduces the overall cost by 2.94–7.68% compared to traditional genetic algorithms, demonstrating superior performance in addressing multi-vehicle, multi-point delivery challenges. |
| format | Article |
| id | doaj-art-d19370f8bb7a495e80d0032dbdeea6f9 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-d19370f8bb7a495e80d0032dbdeea6f92025-08-20T02:50:00ZengNature PortfolioScientific Reports2045-23222024-11-0114112110.1038/s41598-024-78639-1Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumptionHao Chen0Wenxian Wang1Li Jia2Haiming Wang3School of Economics and Business Administration, Yibin UniversitySchool of Rail Transportation, Wuyi UniversitySchool of Rail Transportation, Wuyi UniversityRail Service Center of Jining Transportation BureauAbstract With the increasing demand for fresh food markets, refrigerated transportation has become an essential component of logistics operations. Currently, fresh food transportation frequently faces issues of high energy consumption and high costs, which are inconsistent with the development needs of the modern logistics industry. This paper addresses the optimization problem of multi-vehicle type fresh food distribution under time-varying conditions. It comprehensively considers the changes in road congestion at different times and the quality degradation characteristics of fresh goods during distribution. The objectives include transportation cost, dual carbon cost, and damage cost, subject to constraints such as delivery time windows and vehicle capacity. A piecewise function is used to depict vehicle speeds, proposing a dynamic urban fresh food logistics vehicle routing optimization method. Given the NP-hard nature of the problem, a hybrid Tabu Search (TS) and Genetic Algorithm (GA) approach is designed to compute an optimal solution. Comparison with TS and GA algorithm results shows that the TS-GA algorithm provides the best optimization efficiency and effectiveness for solving large-scale distribution problems. The results indicate that using the TS-GA algorithm to optimize a distribution network with one distribution center and 30 delivery points resulted in a total cost of CNY 12,934.02 and a convergence time of 16.3 s. For problems involving multiple vehicle types and multiple delivery points, the TS-GA algorithm reduces the overall cost by 2.94–7.68% compared to traditional genetic algorithms, demonstrating superior performance in addressing multi-vehicle, multi-point delivery challenges.https://doi.org/10.1038/s41598-024-78639-1Fresh food cold chain distributionTime-varying road congestionDynamic vehicle routing optimizationTabu SearchGenetic algorithm |
| spellingShingle | Hao Chen Wenxian Wang Li Jia Haiming Wang Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption Scientific Reports Fresh food cold chain distribution Time-varying road congestion Dynamic vehicle routing optimization Tabu Search Genetic algorithm |
| title | Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption |
| title_full | Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption |
| title_fullStr | Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption |
| title_full_unstemmed | Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption |
| title_short | Research on time-varying path optimization for multi-vehicle type fresh food logistics distribution considering energy consumption |
| title_sort | research on time varying path optimization for multi vehicle type fresh food logistics distribution considering energy consumption |
| topic | Fresh food cold chain distribution Time-varying road congestion Dynamic vehicle routing optimization Tabu Search Genetic algorithm |
| url | https://doi.org/10.1038/s41598-024-78639-1 |
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