Research on truck-drone collaborative route planning for rural logistics delivery services
Abstract This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics,...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-12-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-83149-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841559433306439680 |
|---|---|
| author | Yong Wang Suo Yang Xi Vincent Wang Lihui Wang |
| author_facet | Yong Wang Suo Yang Xi Vincent Wang Lihui Wang |
| author_sort | Yong Wang |
| collection | DOAJ |
| description | Abstract This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics. Building on this analysis, a collaborative path planning method is proposed, establishing a path optimization model and designing an enhanced simulated annealing algorithm. The effectiveness of this approach is validated through simulation experiments, which reveal that the collaborative delivery system for trucks and drones can significantly boost efficiency, lower costs, and improve service quality. In conclusion, the research findings and potential future research directions are discussed to offer theoretical insights and practical guidance for further innovations in rural logistics technology. |
| format | Article |
| id | doaj-art-5f617e45d0b242f6b7ba90e6f3087e56 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5f617e45d0b242f6b7ba90e6f3087e562025-01-05T12:30:37ZengNature PortfolioScientific Reports2045-23222024-12-0114111410.1038/s41598-024-83149-1Research on truck-drone collaborative route planning for rural logistics delivery servicesYong Wang0Suo Yang1Xi Vincent Wang2Lihui Wang3School of Management, Wuhan University of Science and TechnologySchool of Management, Wuhan University of Science and TechnologyDepartment of Production Engineering, KTH Royal Institute of TechnologyDepartment of Production Engineering, KTH Royal Institute of TechnologyAbstract This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics. Building on this analysis, a collaborative path planning method is proposed, establishing a path optimization model and designing an enhanced simulated annealing algorithm. The effectiveness of this approach is validated through simulation experiments, which reveal that the collaborative delivery system for trucks and drones can significantly boost efficiency, lower costs, and improve service quality. In conclusion, the research findings and potential future research directions are discussed to offer theoretical insights and practical guidance for further innovations in rural logistics technology.https://doi.org/10.1038/s41598-024-83149-1Rural logisticsTrucksDronesCollaborative path planning |
| spellingShingle | Yong Wang Suo Yang Xi Vincent Wang Lihui Wang Research on truck-drone collaborative route planning for rural logistics delivery services Scientific Reports Rural logistics Trucks Drones Collaborative path planning |
| title | Research on truck-drone collaborative route planning for rural logistics delivery services |
| title_full | Research on truck-drone collaborative route planning for rural logistics delivery services |
| title_fullStr | Research on truck-drone collaborative route planning for rural logistics delivery services |
| title_full_unstemmed | Research on truck-drone collaborative route planning for rural logistics delivery services |
| title_short | Research on truck-drone collaborative route planning for rural logistics delivery services |
| title_sort | research on truck drone collaborative route planning for rural logistics delivery services |
| topic | Rural logistics Trucks Drones Collaborative path planning |
| url | https://doi.org/10.1038/s41598-024-83149-1 |
| work_keys_str_mv | AT yongwang researchontruckdronecollaborativerouteplanningforrurallogisticsdeliveryservices AT suoyang researchontruckdronecollaborativerouteplanningforrurallogisticsdeliveryservices AT xivincentwang researchontruckdronecollaborativerouteplanningforrurallogisticsdeliveryservices AT lihuiwang researchontruckdronecollaborativerouteplanningforrurallogisticsdeliveryservices |