基于改进NSGA-Ⅲ算法的车辆路径自动化规划分析  

Analysis of Automated Vehicle Path Planning Based onthe Improved NSGA-ⅢAlgorithm

作　　者：谭信 李寿荣 王翔 李婷 TAN Xin;LI Shourong;WANG Xiang;LI Ting(China Southern Power Grid Digital Platform Technology(Guangdong)Co.,Ltd.,Guangdong 518053,China)

机构地区：[1]南方电网数字平台科技(广东)有限公司,广东518053

出　　处：《自动化与仪器仪表》2025年第2期243-246,251,共5页Automation & Instrumentation

摘　　要：随着物流运输行业的发展,越来越多的物流运输面临运输效率的问题。为此研究针对物流运输中车辆路径自动化规划的问题,提出了一种改进非支配排序遗传算法。新模型对交叉算子、交叉概率和目标函数进行改进分析,提升了模型的车辆路径规划调度和路径数据处理能力。研究结果表明,新模型在车辆调度中有较好的规划效果,其中调度距离最短为2 158 km和1 358 km,相较于其他模型降低了376 km和410 km。同时模型的适配度更高,最高能够达到0.013。由此可见,新模型在车辆路径自动化规划上具有较好的规划效果,这对车辆路径自动化规划的研究具有较好的指导作用。With the development of logistics and transportation industry,more and more logistics transportation faces the problem of transportation efficiency.For this study,an improved non-dominated sorting genetic algorithm is proposed for the problem of auto-mated vehicle path planning in logistics transportation.The new model analyzes the improvement of crossover operator,crossover probability and objective function,which improves the model’s vehicle path planning scheduling and path data processing ability.The results show that the new model has a better planning effect in vehicle scheduling,in which the shortest scheduling distance is 2158 km and 1358 km,compared with other models to reduce the 376 km and 410 km.meanwhile,the model fitness is higher,the highest can reach 0.013.It can be seen that the new model has a better planning effect on vehicle path automation planning,which has a better guiding role in the research of vehicle path automation planning.

关 键 词：车辆路径 自动化 NSGA-Ⅲ 变异算子 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]