Work

Aerial-Ground Collaborative Delivery Route Planning with UAV Energy Function and Multi-Delivery

Year: 2025

Type: article

Abstract: With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile warehouses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to minimize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution augmented large neighborhood search (MEALNS) algorithm incorporating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.

Source: Journal of Systems Engineering and Electronics

DOI: 10.23919/jsee.2025.000048

Authors: Guo Jingfeng, Song Rui, He Shiwei

Institution: Beijing Jiaotong University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funders: National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities