Research on Rural Logistics Path Optimization Based on Collaborative Delivery with Electric Vehicles and Drones

Haoqing Sun and Manhui He ()
Additional contact information
Haoqing Sun: Liaoning Technical University, School of Business and Management
Manhui He: Liaoning Technical University, School of Business and Management

A chapter in Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024), 2024, pp 824-837 from Springer

Abstract: Abstract The rural logistics distribution system faces significant pressure due to the complexity of the terrain and the widespread dispersion of delivery points. To address this challenge, this study innovates upon the traditional single-mode delivery system by proposing a “Electric Vehicle + Drone” collaborative delivery model, which takes into consideration factors such as carbon emissions and customer satisfaction with the goal of minimizing total costs. Initially, the k-means clustering method is used to determine the stopping points of electric vehicles and effectively categorize customer points. Subsequently, an improved ant colony algorithm is employed for route planning. The model’s effectiveness and practicality were verified using the Solomon dataset. Experimental results show that compared to traditional vehicle-only delivery models, the collaborative delivery model excels in reducing total costs by 14.52% and significantly enhances delivery efficiency, with an improvement of 21.86%.

Keywords: Rural Logistics; Drones; Path Optimization; Improved Ant Colony Algorithm (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-570-6_83

Ordering information: This item can be ordered from
http://www.springer.com/9789464635706

DOI: 10.2991/978-94-6463-570-6_83

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().