Optimization of a Cooperative Truck–Drone Delivery System in Rural China: A Sustainable Logistics Approach for Diverse Terrain Conditions
Debao Dai,
Hanqi Cai () and
Shihao Wang
Additional contact information
Debao Dai: School of Management, Shanghai University, Shanghai 200444, China
Hanqi Cai: School of Management, Shanghai University, Shanghai 200444, China
Shihao Wang: Department of Digital Management, Shanghai MAHLE Thermal Systems Co., Ltd., Shanghai 201206, China
Sustainability, 2025, vol. 17, issue 14, 1-26
Abstract:
Driven by the rapid expansion of e-commerce in China, there is a growing demand for high-efficiency, sustainability-oriented logistics solutions in rural regions, particularly for the time-sensitive distribution of perishable agricultural commodities. Traditional logistics systems face considerable challenges in these geographically complex regions due to limited infrastructure and extended travel distances. To address these issues, this study proposes an intelligent cooperative delivery system that integrates automated drones with conventional trucks, aiming to enhance both operational efficiency and environmental sustainability. A mixed-integer linear programming (MILP) model is developed to account for the diverse terrain characteristics of rural China, including forest, lake, and mountain regions. To optimize distribution strategies, the model incorporates an improved Fuzzy C-Means (FCM) algorithm combined with a hybrid genetic simulated annealing algorithm. The performance of three transportation modes, namely truck-only, drone-only, and truck–drone integrated delivery, was evaluated and compared. Sustainability-related externalities, such as carbon emission costs and delivery delay penalties, are quantitatively integrated into the total transportation cost objective function. Simulation results indicate that the cooperative delivery model is especially effective in lake regions, significantly reducing overall costs while improving environmental performance and service quality. This research offers practical insights into the development of sustainable intelligent transportation systems tailored to the unique challenges of rural logistics.
Keywords: sustainable last-mile logistics; truck–drone collaborative delivery; rural terrain-based distribution; cooperative vehicle systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2071-1050/17/14/6390/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/14/6390/ (text/html)
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:gam:jsusta:v:17:y:2025:i:14:p:6390-:d:1700159
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().