基于模拟退火算法的末端车载无人机物流配送路径规划研究  

Research on the logistics and distribution route planning of terminal on-board UAV based on simulated annealing algorithm

作　　者：王芸 WANG Yun(Xi’an Haitang Vocational College,Xi’an 710038,China)

机构地区：[1]西安海棠职业学院,西安710038

出　　处：《自动化与仪器仪表》2025年第2期247-251,共5页Automation & Instrumentation

基　　金：校级教育教学改革项目《高职高专礼仪课程思政路径探析》(HTJG2301)。

摘　　要：针对传统末端车载无人机续航能力低,无人机协同物流配送时无法取得最优路径,导致行驶成本高的问题,提出一种基于改进模拟退火算法(简称I-SA)的末端车载无人机物流配送路径规划方法。首先,搭建一个无人机能量消耗模型和无人机协同物流配送路径优化数学模型,通过模型量化无人机能量消耗,以均衡无人机电池能量消耗与载重续航;然后基于模拟退火算法SA改变局部扰动机制和局部搜索方式,得到改进后的模拟退火算法I-SA;最后将I-SA引入数学模型中实现无人机物流配送最优路径规划。结果表明,I-SA算法与Best的平均偏差值仅为0.9%,明显低于SA算法、蜂群算法和蚁群算法。由此说明I-SA算法的收敛速度更快,搜索质量更好,可提高组合问题的算法性能。在末端无人机物流配送场景下,I-SA算法求解全局最优解可达95%,算法结果波动性小。说明本算法的最优求解能力和稳定性明显优于SA算法和GA算法。在行驶成本测试中,无人机与车辆协同配送的行驶成本均低于传统物流配送,说明提出的算法与构建模型具备普适性,具备实际应用价值。In view of the problem of low driving cost of traditional terminal on-board UAV and the optimal path during UAV co-operative logistics distribution,a terminal on-board UAV logistics distribution path planning method based on the improved simulated annealing algorithm(I-SA)is proposed.First,build a UAV energy consumption model and UAV collaborative logistics distribution path optimization mathematical model to balance the UAV battery energy consumption with the load endurance;then change the local disturbance mechanism and local search method based on the simulated annealing algorithm SA to obtain the improved simulated an-nealing algorithm I-SA;finally,I-SA is introduced into the mathematical model to realize the optimal path planning of UAV logistics distribution.The results show that the average deviation value between I-SA and Best is only 0.9%,which is significantly lower than SA,swarm,and ant colony algorithms.This indicates that the I-SA algorithm converges faster and has better search quality,which can improve the algorithm performance of the combination problem.In the terminal UAV logistics distribution scenario,the I-SA al-gorithm can solve the global optimal solution by 95%,and the algorithm results have little volatility.It shows that the optimal solution ability and stability of this algorithm are significantly better than SA and GA.In the driving cost test,the driving cost of UAV and ve-hicles is lower than that of traditional logistics distribution,indicating that the proposed algorithm and construction model are universal and have practical application value.

关 键 词：模拟退火算法 末端车载 无人机 物流配送 路径规划 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]