多目标多无人机应急物资配送路径规划研究
Research on Multi-objective Path Planning for Emergency Material Delivery by Multi-UAVs
杜晨 1汪勇1
作者信息
- 1. 武汉科技大学管理学院，武汉 430070
- 折叠
摘要
为解决自然灾害后应急物资配送在复杂约束下的时效性与经济性平衡难题，构建多无人机协同配送的双目标优化模型。模型基于三维受灾空间建模，整合无人机性能差异、救灾点时间窗与优先级、障碍物避障等多重约束，以总能耗最小化和覆盖满意度最大化为核心目标，明确任务分配唯一性、载重能量限制等关键约束条件，形成完整数学框架。采用 PSO-ACO两阶段混合算法求解，三种复杂度场景的实验表明，该模型生成的方案平均能耗较 NSGA-II等算法降低18.3%，优先级满意度提升2.3%，计算时间缩短98%以上，且能有效满足多约束要求。结论表明，所提模型可精准适配复杂应急场景，为应急物资无人机配送提供可靠的理论与技术支撑。
Abstract
To address the balance between timeliness and economy of emergency material delivery under complex constraints after natural disasters, a bi-objective optimization model for multi-UAV collaborative delivery is constructed. Based on 3D disaster-stricken space modeling, the model integrates multiple constraints such as differences in UAV performance, time windows and priorities of disaster relief points, and obstacle avoidance. With minimizing total energy consumption and maximizing coverage satisfaction as core objectives, it clarifies key constraints including unique task allocation and load-energy limits, forming a complete mathematical framework. Solved by the PSO-ACO two-stage hybrid algorithm, experiments in three complex scenarios show that the scheme generated by the model reduces average energy consumption by 18.3% compared with algorithms like NSGA-II, improves priority satisfaction by 2.3%, shortens computation time by more than 98%, and effectively meets multiple constraint requirements. The conclusion indicates that the proposed model can accurately adapt to complex emergency scenarios, providing reliable theoretical and technical support for UAV-based emergency material delivery.关键词
多无人机/应急物资配送/PSO-ACO 算法/双目标优化模型Key words
Multi-UAV/Emergency material delivery/PSO-ACO algorithm/Bi-objective optimization model引用本文复制引用
杜晨,汪勇.多目标多无人机应急物资配送路径规划研究[EB/OL].(2026-01-13)[2026-01-18].http://www.paper.edu.cn/releasepaper/content/202601-19.学科分类
航空航天技术/自动化技术、自动化技术设备/计算技术、计算机技术
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