航空学报2025，Vol.46Issue(11)：280-299,20.DOI:10.7527/S1000-6893.2024.31477
城市低空立体物流网络双种群协同优化方法
Dual-population coevolutionary optimization for multi-layer urban air logistics network
摘要
Abstract
Urban Unmanned Aerial Vehicle(UAV)logistics is a significant application for the low-altitude economy,and the Urban Air Logistics(UAL)network is a critical infrastructure for achieving efficient drone delivery.This paper comprehensively considers critical urban factors such as noise constraints,economic costs,and ground safety risks to investigate optimization methodologies for urban air logistics networks.We propose a novel multiobjective mixed-integer programming model that simultaneously minimizes operational costs and ground safety risks while strictly under noise constraints.A dual-population coevolutionary optimization algorithm is developed,which enables knowledge transfer through individual interactions between populations,effectively enhancing the optimization capability of the al-gorithm in irregular solution spaces.Computational experiments show that the proposed algorithm outperforms existing methods with performance improving by over 20%on average.The designed multi-layered network achieves a bal-anced optimum in terms of cost,ground safety risk,and noise.关键词
城市低空物流/网络规划/对地安全风险/无人机噪声/多目标优化/协同进化Key words
urban air logistics/network design/ground safety risk/UAV noise/multiobjective optimization/coevolutionary分类
航空航天引用本文复制引用
张春晓,郭通,李宇萌..城市低空立体物流网络双种群协同优化方法[J].航空学报,2025,46(11):280-299,20.基金项目
北航科研项目基金(23100002022102001) （23100002022102001）
国家自然科学基金(U2333218,52302398,61827901) （U2333218,52302398,61827901）
北京市自然科学基金(L241036) Beihang Research Project(23100002022102001) （L241036）
National Natural Science Foundation of China(U2333218,52302398,61827901) （U2333218,52302398,61827901）
Beijing Natural Science Foundation(L241036) （L241036）
