酿酒葡萄生长过程喷药机田间作业调度研究  

Study on Field Operation Scheduling of Sprayers During Wine Grape Growth

作　　者：李雯[1] 李玉城 周通 Li Wen;Li Yucheng;Zhou Tong(School of Management,Jiangsu University,Zhenjiang 212013,China)

机构地区：[1]江苏大学管理学院,江苏镇江212013

出　　处：《农机化研究》2024年第9期39-45,共7页Journal of Agricultural Mechanization Research

基　　金：国家重点研发计划项目(2019YFD1002500)。

摘　　要：酿酒葡萄产区喷药机的田间调度需求较高,而实际作业中喷药机型号不一、药箱容量不一、转弯速度不一,且传统农机调度研究中很少有针对喷药机田间作业调度的研究。为此,基于车辆路径规划问题(Vehicle Routing Problem,VRP),以成本最小为目标构建酿酒葡萄生长过程喷药机田内作业调度模型,提出改进种马遗传算法(Stud Genetic Algorithm,SGA)进行求解。结合宁夏贺兰山东麓酿酒葡萄产区实际作业田块信息与农机信息进行仿真实验,并与传统遗传算法(Genetic Algorithm,GA)进行对比,结果表明:相比于GA,SGA有着较强的收敛性,不易陷入局部最优;在调度结果上,调度总时间能够缩短3.5%,调度总成本降低6.2%,在实际喷药作业中能在一定程度上节约时间并降低作业成本。At present,the field scheduling demand of sprayers in large wine grape producing areas in China is relatively high,while there are few studies on the field operation scheduling of sprayers in traditional agricultural machinery scheduling research.In this paper,based on the vehicle routing problem(VRP),based on the vehicle routing problem(VRP),the in-field operation scheduling model of the sprayer in the wine grape growth process is constructed with the goal of cost optimization,and the improved stallion genetic algorithm(Stud Genetic Algorithm,SGA)is proposed to solve the operation;Simulation experiments were conducted based on the actual working field information and agricultural machinery information in the eastern foothills of Helan Mountain in Ningxia,and compared with the traditional genetic algorithm(GA).The results show that compared with GA,SGA has strong convergence,is not easy to fall into local optimization,in the scheduling results,the total scheduling time can be shortened by 3.5%,the total scheduling cost can be reduced by 6.2%,in the actual spraying operation of wine grapes can save time and reduce the operation cost to a certain extent.

关 键 词：喷药机 改进种马遗传算法 田间作业调度 酿酒葡萄 

分 类 号：S491[农业科学—植物保护] S232.4