城市低空立体物流网络双种群协同优化方法

  • 张春晓 ,
  • 杜文博 ,
  • 郭通 ,
  • 李宇萌
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  • 北京航空航天大学

收稿日期: 2024-10-31

  修回日期: 2025-03-06

  网络出版日期: 2025-03-12

基金资助

面向“黑飞”反制的多机协同追捕方法研究;面向融合运行的无人机驾驶员在环感知与避撞(DAA)控制机理与效能研究;突发事件下大型枢纽机场综合交通协同调控关键技术研究;低空安全运行关键技术研究及应用;面向有人与无人混合飞行的城市低空数字化空域管理及多智能体仿真

Dual-population Coevolutionary Optimization for the Multi-layer Urban Air Logistics Network

  • ZHANG Chun-Xiao ,
  • DU Wen-Bo ,
  • GUO Tong ,
  • LI Yu-Meng
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Received date: 2024-10-31

  Revised date: 2025-03-06

  Online published: 2025-03-12

摘要

城市无人机物流是低空经济落地应用的重要场景,低空物流网络是其关键基础设施。本文综合考虑噪声约束、经济成本和对地安全风险等因素,开展了城市低空物流网络优化方法研究。在噪声约束下,以最小化经济成本和对地安全风险为优化目标,建立了多目标混合整数规划模型,提出了一种双种群协同进化优化求解算法,通过种群间的个体交互实现知识迁移,有效提升了算法在不规则解空间中的寻优能力。实验表明,本方法与现有方法相比,寻优性能平均提高20%以上,所设计的多高度层立体网络达到了成本、对地安全风险、噪声的均衡最优。

本文引用格式

张春晓 , 杜文博 , 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, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2024.31477

Abstract

Urban unmanned aerial vehicle (UAV) logistics is a significant application for the low-altitude economy, and the urban air logis-tics (UAL) network is a critical infrastructure for achieving efficient drone delivery. This paper comprehensively considers criti-cal urban factors such as noise constraints, economic costs, and ground safety risks to investigate optimization methodologies for urban air logistics (UAL) networks. We propose a novel multiobjective mixed-integer programming model that simultaneously minimizes operational costs and ground safety risks while strictly under noise constraints. To solve the proposed model, a dual-population coevolutionary algorithm is developed, which achieves knowledge transfer through individual interactions between populations and effectively enhance the ability of the algorithm to search for good solutions in irregular solution spaces. Compu-tational experiments show that the proposed algorithm outperforms existing baselines with performance improving more than 20%, respectively. The designed multi-layered network achieves a balanced optimum in terms of cost, ground safety risk, and noise.

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