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智能化农业装备学报（中英文）

智能化农业装备学报（中英文） ›› 2022, Vol. 3 ›› Issue (2): 1-9.DOI: 10.12398/j.issn.2096-7217.2022.02.001

• •    下一篇

基于模拟退火算法的飞防队调度模型研究

李亦白, 曹光乔   

  1. 农业农村部南京农业机械化研究所，江苏南京，210014
  • 出版日期:2022-11-15 发布日期:2022-11-15
  • 通讯作者: 曹光乔
  • 作者简介:李亦白，硕士，助理研究员，研究方向为农业机械调度。E-mail: lyb19940209@163.com

Research on the scheduling model of flying defense team based on simulated annealing algorithm

Li Yibai, Cao Gunagqiao   

  1. Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China
  • Online:2022-11-15 Published:2022-11-15
  • Contact: Cao Guangqiao
  • About author:Li Yibai, Master, Assistant Professor, research interests: agricultural machinery scheduling model. E-mail: lyb19940209@163.com
  • Supported by:
    A Grant of the Special Funding for Basic Scientific Research Business Expenses of Central Public Welfare Scientific Research Institutes (S202010, S20210902); Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences (Academy of Agricultural Sciences Office (2014) No.216)

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摘要： 植保无人机作业通常以飞防队形式进行作业，目前飞防队调度组织形式较为粗犷，造成飞防队整体效率较低的问题，合理调度无人机可提高飞防队的作业效率。以水稻稻曲病防治场景为研究对象，根据水稻稻曲病“三喷一防”的作业规范，结合现有飞防作业订单模式现状，为保障植保无人机的作业质量与作业效率，提出了订单管理与植保无人机调度模型。模型主要分为2个部分。（1）订单管理。综合考虑订单作业面积、时间窗、订单紧急程度的订单排序方法。（2）调度模型。基于模拟退火算法的无人机调度模型。以南京地区16个地块，4个飞防队的水稻稻曲病防治作业任务为例，分别在时间窗间隔为3~6 d的情况下，使用模拟退火算法与贪婪算法进行比较。结果表明，模拟退火算法在总作业收益、无人机等待时间与调度距离上较贪婪算法都更具优势。时间窗间隔在3~5 d内，时间窗越长，调度路程和等待时间越短，总作业时间越长，总收益越高。时间窗长度为6 d时，作业总时长与作业收益不再改变。该研究可为无人机飞防队的调配与决策分析提供科学依据,为农机智能调度系统开发提供参考。


关键词: 植保无人机, 调度模型, 任务分配, 模拟退火算法

Abstract: Plant protection UAVs (unmanned aerial vehicles) are usually operated in the form of flying defense teams. At present, the scheduling organization of the flying defense teams is relatively extensive, resulting in the low efficiency of the flying defense teams. Reasonable scheduling of UAVs can improve the operational efficiency of the flying defense teams. By taking the rice smut prevention and control scenarios as the research object, according to the operation specifications of “single-spray triple-prevention” against rice smut, referring to the current situation of the order modes of flying defense operation, an order management and plant protection UAVs scheduling model is proposed in this study, to ensure the operation quality and operation efficiency of plant protection UAVs. The model has two parts: (1) Order management, which is an order sorting method that comprehensively considers order work area, time window, and order urgency; (2) Scheduling model, which is a UAV scheduling model based on simulated annealing algorithm. Taking 16 plots in Nanjing area in China and rice smut control tasks of 4 flying defense teams for case study, the simulated annealing algorithm and the greedy algorithm were used to make a comparative study on the time window lengths of 3-6 days. Research results showed that, when the operation time window length is 3-5 days, the longer the time window, the shorter the scheduling distance and waiting time, the longer the total operation time, and the higher the total revenue. When the time window length is 6 days, the total operation time and operation income will not change. This research can provide a scientific basis for the deployment and decision-making analysis of the UAVs flying defense teams, and provide a reference for the development of the intelligent scheduling system for agricultural machinery.

Key words: plant protection unmanned aerial vehicles, scheduling model, task assignment, simulated annealing algorithm

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