Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers
Abstract Industrial enterprises have high requirements on timeliness and cost when delivering industrial products to their customers. For this reason, this paper studies the vehicle routing problem (VRP) of different vehicle models in multiple distribution centers. First of all, we consider the mult...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-08-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-41450-5 |
| _version_ | 1827634912131284992 |
|---|---|
| author | Zhaolei He Miaohan Zhang Qiyong Chen Shiyun Chen Nan Pan |
| author_facet | Zhaolei He Miaohan Zhang Qiyong Chen Shiyun Chen Nan Pan |
| author_sort | Zhaolei He |
| collection | DOAJ |
| description | Abstract Industrial enterprises have high requirements on timeliness and cost when delivering industrial products to their customers. For this reason, this paper studies the vehicle routing problem (VRP) of different vehicle models in multiple distribution centers. First of all, we consider the multi-dimensional constraints in the actual distribution process such as vehicle load and time window, and build a multi-objective optimization model for product distribution with the goal of minimizing the distribution time and cost and maximizing the loading rate of vehicles. Furthermore, an Improved Life-cycle Swarm Optimization (ILSO) algorithm is proposed based on the life cycle theory. Finally, we use the order data that Yunnan Power Grid Company needs to deliver to the customer (municipal power supply bureau) on a certain day to conduct a dispatching experiment. The simulation and application results show that the transportation cost of transportation obtained by the ILSO algorithm is reduced by 0.8% to 1.6% compared with the other five algorithms. Therefore, ILSO algorithm has advantages in helping enterprises reduce costs and improve efficiency. |
| first_indexed | 2024-03-09T15:20:52Z |
| format | Article |
| id | doaj.art-d272a187b73d4bb8b356821454c25e74 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:20:52Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-d272a187b73d4bb8b356821454c25e742023-11-26T12:51:38ZengNature PortfolioScientific Reports2045-23222023-08-0113112010.1038/s41598-023-41450-5Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centersZhaolei He0Miaohan Zhang1Qiyong Chen2Shiyun Chen3Nan Pan4Metrology Center, Yunnan Power Grid Co., LtdFaculty of Civil Aviation and Aeronautics, Kunming University of Science and TechnologyFaculty of Civil Aviation and Aeronautics, Kunming University of Science and TechnologyFaculty of Civil Aviation and Aeronautics, Kunming University of Science and TechnologyFaculty of Civil Aviation and Aeronautics, Kunming University of Science and TechnologyAbstract Industrial enterprises have high requirements on timeliness and cost when delivering industrial products to their customers. For this reason, this paper studies the vehicle routing problem (VRP) of different vehicle models in multiple distribution centers. First of all, we consider the multi-dimensional constraints in the actual distribution process such as vehicle load and time window, and build a multi-objective optimization model for product distribution with the goal of minimizing the distribution time and cost and maximizing the loading rate of vehicles. Furthermore, an Improved Life-cycle Swarm Optimization (ILSO) algorithm is proposed based on the life cycle theory. Finally, we use the order data that Yunnan Power Grid Company needs to deliver to the customer (municipal power supply bureau) on a certain day to conduct a dispatching experiment. The simulation and application results show that the transportation cost of transportation obtained by the ILSO algorithm is reduced by 0.8% to 1.6% compared with the other five algorithms. Therefore, ILSO algorithm has advantages in helping enterprises reduce costs and improve efficiency.https://doi.org/10.1038/s41598-023-41450-5 |
| spellingShingle | Zhaolei He Miaohan Zhang Qiyong Chen Shiyun Chen Nan Pan Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers Scientific Reports |
| title | Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers |
| title_full | Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers |
| title_fullStr | Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers |
| title_full_unstemmed | Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers |
| title_short | Optimization of heterogeneous vehicle logistics scheduling with multi-objectives and multi-centers |
| title_sort | optimization of heterogeneous vehicle logistics scheduling with multi objectives and multi centers |
| url | https://doi.org/10.1038/s41598-023-41450-5 |
| work_keys_str_mv | AT zhaoleihe optimizationofheterogeneousvehiclelogisticsschedulingwithmultiobjectivesandmulticenters AT miaohanzhang optimizationofheterogeneousvehiclelogisticsschedulingwithmultiobjectivesandmulticenters AT qiyongchen optimizationofheterogeneousvehiclelogisticsschedulingwithmultiobjectivesandmulticenters AT shiyunchen optimizationofheterogeneousvehiclelogisticsschedulingwithmultiobjectivesandmulticenters AT nanpan optimizationofheterogeneousvehiclelogisticsschedulingwithmultiobjectivesandmulticenters |