基于人工智能算法的柔性生产车间设备与AGV小车协同规划方法

Jin-Ping Du Jin-Ping Du, Xiao-Fei Wu Jin-Ping Du, Jian Wang Xiao-Fei Wu, Dong-Liang Fan Jian Wang, Qian-Han Zhang Dong-Liang Fan
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引用次数: 0

摘要

针对当前柔性生产车间AGV小车规划存在路径冲突、规划目标单一、规划阶段隔离等问题,提出了包括AGV运行时间、生产车间能耗和机器运行效率在内的多目标函数。然后,利用飞行鼠标算法实现多函数求解。为了避免在求解过程中陷入局部最优,在飞鼠算法中引入了模拟退火策略。最后,以新能源汽车车载电池生产为例,运用本文提出的方法进行协同规划分析。结果表明,本文提出的算法可节省30%的运行时间,提高机器运行效率22.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collaborative Planning Method for Flexible Production Workshop Equipment and AGV Trolley Based on Artificial Intelligence Algorithms
This article proposes a multi-objective function that includes AGV running time, production workshop energy consumption, and machine running efficiency, in response to the problems of path conflicts, single planning objectives, and isolation of planning stages in the current flexible production workshop AGV car planning. Then, the flying mouse algorithm is used to solve the problem using multiple functions. In order to avoid falling into local optima during the solving process, a simulated annealing strategy is incorporated into the flying mouse algorithm. Finally, taking the production of new energy vehicle on-board batteries as an example, a collaborative planning analysis was conducted using the method proposed in this paper. The results showed that the algorithm proposed in this paper can save 30% of running time and improve machine operating efficiency by 22.7%.  
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