摘要
针对城市物流无人机起降点布局规划问题,考虑不同级别的物流无人机起降点,构建以总经济成本最小和客户满意度最高为目标,以禁飞区、无人机性能、容需匹配等为约束的整数规划模型。设计人类学习优化算法(HLO),引入随机学习算子、个体学习算子和社会学习算子。在此基础上,基于真实地理信息数据和物流数据设计仿真实验,验证模型与算法有效性。实验结果表明,所建模型可以实现起降点的合理布局规划,适用于大规模资源配置,具备有效性;人类学习优化算法较遗传算法求解精度与收敛速度更优,表现出较佳性能。参数分析表明,基于该仿真环境的最优经济成本权重和客户满意度权重设置为0.4和0.6,最佳算法学习概率参数组合为5/n和(0.8+2/n)。据此可对城市物流无人机起降点布局规划提供决策依据。
This paper focuses on the layout planning of urban logistics Unmanned Aerial Vehicle(UAV) vertiports.In consideration of different types of logistics UAV vertiports,this paper proposes a vertiports layout planning model with the objective of minimizing the total economic cost and maximizing the customer satisfaction.The constraints of the model involve no-fly zone,UAV performance,vertiport capacity,and other factors.The human learning optimization algorithm(HLO) is designed and the random learning operator,individual learning operator and social learning operator are introduced in the algorithm to solve the model.The simulation experiment is then performed with real geographic data and logistics data to verify the effectiveness of the model and algorithm.The experimental results show that the proposed model can generate reasonable layout planning of vertiports,which is suitable and effective for large-scale resource allocation problem.The HLO algorithm shows better solution accuracy and convergence speed than the genetic algorithm(GA) The parameter analysis shows that the optimal economic cost weight is 0.4 and the optimal customer satisfaction weight is 0.6 based on the simulation environment.The optimal algorithm learning probability parameters are 5/n and 0.8 + 2/n.The study results could provide decision-making support for the layout planning of the actual urban logistics UAV vertiports.
作者
张洪海
冯棣坤
张晓玮
刘皞
钟罡
张连东
ZHANG Hong-hai;FENG Di-kun;ZHANG Xiao-wei;LIU Hao;ZHONG Gang;ZHANG Lian-dong(School of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2022年第3期207-214,共8页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(71971114)
南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20200716)。
关键词
航空运输
起降点布局规划
人类学习优化算法
物流无人机
物流配送
air transportation
layout planning of vertiports
human learning optimization algorithm
logistics Unmanned Aerial Vehicle(UAV)
logistics distribution
