Cooperative trucks and drones for rural last-mile delivery with steep roads

• Main Authors: XIAO, Jiuhong, LI, Ying, CAO, Zhiguang, XIAO, Jianhua
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Adaptive large neighborhood search; Cooperative delivery; Energy consumption; Steep roads; Trucks and drones; Numerical Analysis and Scientific Computing; Operations Research, Systems Engineering and Industrial Engineering; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/8553; https://ink.library.smu.edu.sg/context/sis_research/article/9556/viewcontent/CooperativeTrucksDrones_av.pdf
• Institution: Singapore Management University

The cooperative delivery of trucks and drones promises considerable advantages in delivery efficiency and environmental friendliness over pure fossil fuel fleets. As the prosperity of rural B2C e-commerce grows, this study intends to explore the prospect of this cooperation mode for rural last-mile delivery by developing a green vehicle routing problem with drones that considers the presence of steep roads (GVRPD-SR). Realistic energy consumption calculations for trucks and drones that both consider the impacts of general factors and steep roads are incorporated into the GVRPD-SR model, and the objective is to minimize the total energy consumption. To solve the proposed model, an improved adaptive large neighborhood search (IALNS) algorithm is introduced, which incorporates several novel operators designed based on the characteristics of the problem. The effectiveness of the IALNS algorithm and the feasibility of the GVRPD-SR are verified through extensive computational experiments. Furthermore, a detailed sensitivity analysis is conducted on several critical parameters to derive managerial insights.