Task assignment of multiple agricultural machinery cooperation based on improved ant colony algorithm

任务(项目管理) 蚁群优化算法 计算机科学 过程(计算) 背景(考古学) 路径(计算) 集合(抽象数据类型) 蚁群 算法 分配问题 运筹学 数学优化 工程类 数学 系统工程 生物 古生物学 程序设计语言 操作系统
作者
Ruyue Cao,Shichao Li,Yuhan Ji,Zhenqian Zhang,Hongzhen Xu,Man Zhang,Minzan Li,Han Li
出处
期刊:Computers and Electronics in Agriculture [Elsevier BV]
卷期号:182: 105993-105993 被引量:61
标识
DOI:10.1016/j.compag.2021.105993
摘要

Abstract Task assignment is a key problem in multi-machine cooperative navigation. In the context of regional farmland operation, multiple agricultural machines often need to complete multiple tasks together. In order to realize the management of multiple agricultural machinery cooperation, studies on task assignment based on the improved ant colony algorithm have been conducted under the farmland operation environment. First, a task assignment model of multiple agricultural machinery cooperation was established by combining dynamic and static task assignments. Then, according to the task assignment model, the task assignment process based on the improved ant colony algorithm was established while considering the match between supply and demand, the operation capacity of the agricultural machinery, and the operation cycle and path cost. Finally, the dynamic and static task assignments of multiple agricultural machinery cooperation based on the improved ant colony algorithm were simulated on MATLAB. Taking the crop harvesting experiment as an example, according to the actual farmland location information of the Zhuozhou Experimental Farm, the different (agricultural machinery, task) combinations were set, and the task assignment results were compared and analyzed. Results showed that the path costs of harvester and grain transporters were reduced by 51.27% and 22.00% respectively, When the quantities of tasks were set to 11, indicating that the improved ant colony algorithm can effectively reduce the path cost. When the quantities of tasks were set to 5, 11, 16 and 22, the average operation cycles were shortened by 67.32%, 37.50%, 55.95%, and 56.37% respectively. The problem of “nearby” in the task assignment was solved to a certain extent, the overload of some agricultural machinery and the idle of other agricultural machinery were avoided, and the operation cycle was shortened. At the same time, based on the static task assignment, the dynamic task assignment was realized in the two scenarios of new tasks and malfunctioning harvesters, thus laying a foundation for further solving the scheduling management problem of multiple agricultural machinery cooperation under a complex farmland operation environment.
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