低空经济时代电商末端物流的配送路径优化

Delivery Route Optimization for E-Commerce Last-Mile Logistics in the Era of Low-Altitude Economy

摘要: 在低空经济快速崛起、电商物流配送向智能化、无人化升级的背景下，无人机作为低空物流的核心载体，其路径规划的合理性直接影响电商末端配送的效率、成本与安全性，更是推动低空经济与电子商务深度融合的关键技术支撑。本文针对电商末端物流配送场景下的三维无人机路径规划问题，以飞行距离、高度变化、安全和平滑性为核心约束条件，构建多目标成本函数并设计改进淘金优化算法(IGRO)用于寻找最优配送路径。通过仿真实验验证IGRO相较于原淘金优化算法，路径规划总成本平均减少40.1%。且相较于其他对比算法，不仅具备最优的路径规划效果，还拥有最快的收敛速度，充分证明本文构建的路径规划模型与改进算法的有效性和实用性，助力打通低空经济背景下电商末端配送最后一公里瓶颈。

Abstract: Against the backdrop of the rapid rise of the low-altitude economy and the upgrading of e-commerce logistics distribution towards intelligence and unmanned operation, drones, as the core carrier of low-altitude logistics, their reasonable path planning directly determines the efficiency, cost and safety of e-commerce terminal distribution, and is also a key technical support for promoting the in-depth integration of the low-altitude economy and e-commerce. Aiming at the 3D UAV path planning problem in the scenario of e-commerce terminal logistics distribution, this paper takes flight distance, flight altitude, flight safety and smoothness as the core constraints, constructs a multi-objective cost function and designs an Improved Gold Rush Optimization algorithm (IGRO) to find the optimal distribution path. Simulation experiments verify that compared with the original Gold Rush Optimization (GRO) algorithm, the total path planning cost of the IGRO algorithm is reduced by an average of 40.1%. Moreover, compared with other comparative algorithms, it not only has the optimal path planning effect, but also has the fastest convergence speed, which fully proves the effectiveness and practicality of the path planning model and improved algorithm constructed in this paper, helping to break through the bottleneck of the last mile in e-commerce terminal distribution under the background of the low-altitude economy.