Work

UAV Route Optimization for Rural Logistics Considering Energy Consumption and Time-Window Constraints

Year: 2026

Type: book-chapter

Abstract: Rural logistics is challenged by complex terrain, dispersed demand, and fluctuating UAV energy use. This study investigates UAV route optimization for rural logistics in Zhongyangping Village, Zigui County, Hubei Province, by incorporating refined energy consumption and soft time-window constraints. A refined energy model is developed by considering wind conditions, terrain slope, and payload, with total energy divided into takeoff-and-landing energy and cruising energy. Soft time windows are introduced based on rural residents’ daily routines and service-point schedules. On this basis, a UAV routing optimization model is established to minimize total operating cost, and an improved genetic algorithm with cluster-based optimization and neighborhood mutation is proposed. Results show that the proposed model reduces energy cost by 18.2% compared with a linear distance-based model and by 82.0% compared with a simple payload-based model. The algorithm converges stably within 200 generations, demonstrating strong solution quality and practical applicability.

Source: Frontiers in artificial intelligence and applications

DOI: 10.3233/faia260689

Authors: Yong Wang, Yafei Wu, Qian Lu, Xi Vincent Wang, Lihui Wang

Institutions: Wuhan University of Science and Technology, KTH Royal Institute of Technology, Cyberspace Security University of China

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities

Open Access status: hybrid

OpenAlex ID: W7204598408

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