Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility
Urban road networks are prone to disruptions that can result in localized congestion or even complete interruptions, thereby causing delays in conventional logistics distribution. To mitigate this issue, the present study proposes a dynamic deployment model and task planning methodology for vehicle–...
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MDPI AG
2025-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/11/6322 |
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| author | Wei Qi Ang Li Honghai Zhang |
| author_facet | Wei Qi Ang Li Honghai Zhang |
| author_sort | Wei Qi |
| collection | DOAJ |
| description | Urban road networks are prone to disruptions that can result in localized congestion or even complete interruptions, thereby causing delays in conventional logistics distribution. To mitigate this issue, the present study proposes a dynamic deployment model and task planning methodology for vehicle–drone collaborative delivery in areas affected by road disruptions. Utilizing complex network theory, a framework for identifying node vulnerabilities within road networks is established. Furthermore, a dynamic model for selecting drone take-off and landing sites, as well as task planning, is developed with the dual objectives of minimizing delivery costs and time while maximizing demand coverage. An enhanced evolutionary algorithm is devised to address the model. Results from case studies indicate that when the failure rate of regional road network nodes reaches 50%, the network vulnerability value is 0.8, achieving an air–ground collaborative logistics task completion rate of 95% and a delivery time of approximately 120 min. Conversely, when node failure escalates to 70%, the vulnerability value approaches 1.0, while still achieving a 90% task completion rate and a delivery time of 150 min. The proposed air–ground collaborative dynamic logistics approach effectively addresses distribution challenges in disrupted road networks and offers technical support for the advancement of urban low-altitude logistics. |
| format | Article |
| id | doaj-art-d67c2ae1765c4f9db499b5d7d606880e |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-d67c2ae1765c4f9db499b5d7d606880e2025-08-20T02:32:51ZengMDPI AGApplied Sciences2076-34172025-06-011511632210.3390/app15116322Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network FragilityWei Qi0Ang Li1Honghai Zhang2College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 213300, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 213300, ChinaUrban road networks are prone to disruptions that can result in localized congestion or even complete interruptions, thereby causing delays in conventional logistics distribution. To mitigate this issue, the present study proposes a dynamic deployment model and task planning methodology for vehicle–drone collaborative delivery in areas affected by road disruptions. Utilizing complex network theory, a framework for identifying node vulnerabilities within road networks is established. Furthermore, a dynamic model for selecting drone take-off and landing sites, as well as task planning, is developed with the dual objectives of minimizing delivery costs and time while maximizing demand coverage. An enhanced evolutionary algorithm is devised to address the model. Results from case studies indicate that when the failure rate of regional road network nodes reaches 50%, the network vulnerability value is 0.8, achieving an air–ground collaborative logistics task completion rate of 95% and a delivery time of approximately 120 min. Conversely, when node failure escalates to 70%, the vulnerability value approaches 1.0, while still achieving a 90% task completion rate and a delivery time of 150 min. The proposed air–ground collaborative dynamic logistics approach effectively addresses distribution challenges in disrupted road networks and offers technical support for the advancement of urban low-altitude logistics.https://www.mdpi.com/2076-3417/15/11/6322complex networkvulnerabilityair-ground collaborationimproved evolutionary algorithm |
| spellingShingle | Wei Qi Ang Li Honghai Zhang Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility Applied Sciences complex network vulnerability air-ground collaboration improved evolutionary algorithm |
| title | Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility |
| title_full | Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility |
| title_fullStr | Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility |
| title_full_unstemmed | Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility |
| title_short | Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility |
| title_sort | research on dynamic planning method for air ground collaborative last mile delivery considering road network fragility |
| topic | complex network vulnerability air-ground collaboration improved evolutionary algorithm |
| url | https://www.mdpi.com/2076-3417/15/11/6322 |
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