Multi-Compartment Electric Vehicle Routing Problem for Perishable Products
The study first proposes a heterogeneous fleet, multi-compartment electric vehicle routing problem for perishable products (MCEVRP-PP). We capture a lot of practical demands and constraints of the MCEVRP-PP, such as multiple temperature zones, the hard time window, charging more than once during del...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2024-03-01
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| Series: | International Journal of Crowd Science |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/IJCS.2023.9100017 |
| _version_ | 1797202640110616576 |
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| author | Zhishuo Liu Yuqing Li Junzhe Xu Donglu Bai |
| author_facet | Zhishuo Liu Yuqing Li Junzhe Xu Donglu Bai |
| author_sort | Zhishuo Liu |
| collection | DOAJ |
| description | The study first proposes a heterogeneous fleet, multi-compartment electric vehicle routing problem for perishable products (MCEVRP-PP). We capture a lot of practical demands and constraints of the MCEVRP-PP, such as multiple temperature zones, the hard time window, charging more than once during delivery, various power consumption per unit of refrigeration, etc. We model the MCEVRP-PP as a mixed integer program and aim to optimize the total cost including vehicle fixed cost, power cost, and cooling cost. A hybrid ant colony optimization (HACO) is developed to solve the problem. In the transfer rule, the time window is introduced to improve flexibility in route construction. According to the features of multi-compartment electric vehicles, the capacity constraint judgment algorithm is developed in route construction. Six local search strategies are designed with time windows, recharging stations, etc. Experiments based on various instances validate that HACO solves MCEVRP-PP more effectively than the ant colony optimization (ACO). Compared with fuel vehicles and single-compartment vehicles, electric vehicles and multi-compartment electric vehicles can save the total cost and mileage, and increase utilization of vehicles. |
| first_indexed | 2024-04-24T08:06:39Z |
| format | Article |
| id | doaj.art-ef82345f95794ca9a177b98315182fc0 |
| institution | Directory Open Access Journal |
| issn | 2398-7294 |
| language | English |
| last_indexed | 2024-04-24T08:06:39Z |
| publishDate | 2024-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | International Journal of Crowd Science |
| spelling | doaj.art-ef82345f95794ca9a177b98315182fc02024-04-17T10:35:55ZengTsinghua University PressInternational Journal of Crowd Science2398-72942024-03-0181384810.26599/IJCS.2023.9100017Multi-Compartment Electric Vehicle Routing Problem for Perishable ProductsZhishuo Liu0Yuqing Li1Junzhe Xu2Donglu Bai3School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaThe study first proposes a heterogeneous fleet, multi-compartment electric vehicle routing problem for perishable products (MCEVRP-PP). We capture a lot of practical demands and constraints of the MCEVRP-PP, such as multiple temperature zones, the hard time window, charging more than once during delivery, various power consumption per unit of refrigeration, etc. We model the MCEVRP-PP as a mixed integer program and aim to optimize the total cost including vehicle fixed cost, power cost, and cooling cost. A hybrid ant colony optimization (HACO) is developed to solve the problem. In the transfer rule, the time window is introduced to improve flexibility in route construction. According to the features of multi-compartment electric vehicles, the capacity constraint judgment algorithm is developed in route construction. Six local search strategies are designed with time windows, recharging stations, etc. Experiments based on various instances validate that HACO solves MCEVRP-PP more effectively than the ant colony optimization (ACO). Compared with fuel vehicles and single-compartment vehicles, electric vehicles and multi-compartment electric vehicles can save the total cost and mileage, and increase utilization of vehicles.https://www.sciopen.com/article/10.26599/IJCS.2023.9100017multiple compartmentselectric vehiclecold chain logisticsheterogeneous fleetvehicle routing problemhybrid ant colony optimization |
| spellingShingle | Zhishuo Liu Yuqing Li Junzhe Xu Donglu Bai Multi-Compartment Electric Vehicle Routing Problem for Perishable Products International Journal of Crowd Science multiple compartments electric vehicle cold chain logistics heterogeneous fleet vehicle routing problem hybrid ant colony optimization |
| title | Multi-Compartment Electric Vehicle Routing Problem for Perishable Products |
| title_full | Multi-Compartment Electric Vehicle Routing Problem for Perishable Products |
| title_fullStr | Multi-Compartment Electric Vehicle Routing Problem for Perishable Products |
| title_full_unstemmed | Multi-Compartment Electric Vehicle Routing Problem for Perishable Products |
| title_short | Multi-Compartment Electric Vehicle Routing Problem for Perishable Products |
| title_sort | multi compartment electric vehicle routing problem for perishable products |
| topic | multiple compartments electric vehicle cold chain logistics heterogeneous fleet vehicle routing problem hybrid ant colony optimization |
| url | https://www.sciopen.com/article/10.26599/IJCS.2023.9100017 |
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