城市物流无人机配送中心选址及任务分配研究  

Research on location and task allocation of urban logistics UAV distribution center

作　　者：刘光才[1] 马寅松 LIU Guangcai;MA Yinsong(College of Transportation Science and Engineering,CAUC,Tianjin 300300,China)

机构地区：[1]中国民航大学交通科学与工程学院,天津300300

出　　处：《飞行力学》2023年第3期88-94,共7页Flight Dynamics

基　　金：国家软科学研究计划资助(2013GXS4B094)。

摘　　要：针对城市场景下物流无人机配送中心选址及任务分配问题进行了研究。首先,以经济总成本最小和时间可靠性最大为目标,综合考虑禁飞区空域限制和无人机自身性能构建了多约束条件下的无人机配送中心选址及任务分配模型。然后,设计了一种改进模拟退火遗传算法进行快速求解,并通过定义各目标函数的隶属度函数,引入自适应交叉概率,以适应度值为依据进行退温操作等方法提升算法的全局性和局部搜索能力。最后,经对照实验得出各代价权重取值的最优组合以及不同的空域环境条件对最终结果的影响。研究结果表明,模型可以实现预期效果,该算法在应对此类问题时具有良好的适应性。The problem of location and task allocation of urban logistics UAV distribution center is studied.Firstly,aiming at the minimum total economic cost and the maximum time reliability,considering the no-fly zone airspace restrictions and the performance of UAV,a location and task allocation planning model for logistics UAV distribution center under multiple constraints was established.Then,an improved simulated annealing-genetic algorithm was designed to solve the model quickly.In order to improve the ability of global and local search,this paper proposed some methods such as defining the membership function of each objective function,introducing the adaptive crossover rate,and performing the cooling operation based on the fitness value.Finally,the comparative experiment analysis showed the best combination of each cost weight value and the impact of different airspace environmental conditions on the final result.The research results show that the proposed model can achieve the expected performance,the proposed algorithm has a good adaptability to deal with such problems.

关 键 词：物流无人机 多目标函数 配送中心选址 任务分配 改进模拟退火遗传算法 

分 类 号：F252.1[经济管理—国民经济] V353[航空宇航科学与技术—人机与环境工程]