机群协同作业路径动态优化

姚竟发; 刘静; 滕桂法; 张璠; 范晓飞

doi:10.13733/j.jcam.issn.2095-5553.2021.06.17

机群协同作业路径动态优化

姚竟发^1,2,
刘静³,
滕桂法^2,4,
张璠^2,4,
范晓飞^1,

1. 河北农业大学机电工程学院;
2. 河北农业大数据重点实验室;
3. 保定理工学院基础课教学部;
4. 河北农业大学信息科学与技术学院

基金项目:

河北省重点研发计划项目(19227210D、20327403D)

河北省自然科学基金项目(G2018204093)

河北省高等学校科学技术研究项目(BJ2018012)

详细信息

作者简介:
姚竟发,男,1983年生,河北衡水人,博士,讲师,研究方向为人工智能与数字农业。E-mail:knorray@163.com

通讯作者:
范晓飞,男,1963年生,河北张家口人,博士,教授,博导,研究方向为农业信息化与人工智能。E-mail:fanxiaofei@hebau.edu.cn

中图分类号: S220
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出版历程
- 收稿日期: 2021-02-20
- 刊出日期: 2021-06-14

Dynamic optimization of cooperative operation path for agricultural machinery fleet

1. College of Mechanical and Electrical Engineering, Hebei Agricultural University;
2. Hebei Province Key Laboratory of Agricultural Big Data;
3. Basic Teaching Department, Baoding University of Technology;
4. College of Information Science and Technology, Hebei Agricultural University

摘要

摘要: 随着我国农业机械化不断发展,智能农机应运而生,其作业路径被农机大数据中心实时监测、调控。合理的作业路径不仅可以提高作业效率,而且当车队运行状态或农田环境改变后,能实现精准作业,因此,研究如何动态优化车队协同作业具有十分重要的理论意义和实用价值。以总作业时间和作业时长综合最短为优化目标,同时避免作业冲突,构建机群协同作业路径动态优化模型,设计冲突检测规则,提出一种机群协同作业路径动态优化(DOFOP)算法。试验结果表明,当有农机发生故障时,重新优化后的作业时长、总作业时间比并排作业均减少2.52%,平均作业农田能力AEFC、农田效率FE比并排作业平均提高2.63%、2.59%;当有农机作业速率发生改变时,重新优化后的作业时长、总作业时间比原作业分别降低7.22%、2.73%,AEFC、FE比原作业分别提高7.99%、2.82%;当农田面积发生改变时,重新优化后的作业时长、总作业时间比原作业降低6.26%、0.1%,AEFC、FE比原作业分别提高6.48%、0.1%。当机群作业状态发生改变时,DOFOP算法能有效动态优化机群作业路径,提高机群作业效率,实现机群精准作业。
- 智能农机 /
- 机群 /
- 协同作业 /
- 动态优化 /
- 作业冲突
Abstract: With the development of agricultural mechanization, intelligent agricultural machinery emerges as time requires. The operation path of the fleet is monitored and regulated by a big data center of agricultural machinery in real-time. A reasonable operation path can improve the efficiency of operation and achieve accurate operation when the fleet operation state or farmland environment changes. Therefore, it is of great theoretical significance and practical value to study how to optimize the cooperative operation of the fleet dynamically. In this paper, the optimization aims to minimize the total time and completion time of operation and avoid job conflicts. Firstly, a dynamic optimization model of the fleet cooperative operation path is constructed, and the conflict detection rules are designed. Then, a dynamic optimization algorithm, DOFOP, is proposed. The test results showed that when there was a failure of agricultural machinery, the completion time and total time of the re-optimized operation were reduced by 2.52% compared to the parallel operation, and the AEFC and FE were increased by 2.63% and 2.59% on average compared to the parallel operation. When there was a change in the operation rate of agricultural machinery, the operation time and total operation time of the re-optimized operation were reduced by 7.22% and 2.73%, respectively, and the AEFC and FE were lower than the original operation. When the farmland area changed, the operation time and total operation time decreased by 6.26% and 0.1%, and the AEFC and EF increased by 6.48% and 0.1%, respectively. When the operation status of the fleet changes, the DOFOP algorithm can effectively and dynamically optimize the operation path of the fleet, improve the efficiency of the fleet operation, and achieve the precise operation of the fleet.
- intelligent agricultural machinery /
- fleet /
- collaborative operation /
- dynamic optimization /
- operation conflict

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参考文献(26)

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