基于多AGV的自动化仓储系统仿真研究
首发时间:2019-09-09
摘要:对自动化仓储系统中的任务繁忙度进行了定义,提出了系统任务繁忙度的求解方法;并利用已获数据中的AGV取货完成到放货完成的运行时间运用BP神经网络对系统拥堵时间进行拟合;最后利用导轨布局网络图构建网络模型,结合WMS/WCS系统的控制变量和现行任务排队策略对任务下发到AGV取货完成时间构建仿真模型,用流水数据校对模型。建立了一套AGV仓储系统的仿真模型,以便为新环境中的仓储决策提供测试平台。仿真结果表明,任务从下发到AGV取货完成时间均值为1.8632,标准差为0.9683,而现实数据的均值为1.7898,标准差为0.7928。上述仿真结果表明本文所建模型对实际多AVG仓储系统进行了较好的模拟。
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Simulation Research on Automated Warehousing System Based on Multi-AGV
Abstract:Defined the task busyness in the automated warehouse system and proposed the solution method of it . Then using the BP neural network to fit the system congestion time by using the time AGV pick-up to complete the delivery in the acquired data. Finally, using the rail layout network diagram construct the network model, combining with the control variables of the WMS/WCS system and the current task queuing strategy build a simulation model about the time that task is sent until AGV finished picking up the task, then the flow data is used to proofread the model. A simulation model of the AGV warehousing system was established to provide a test platform for warehousing decisions in the new environment. The simulation results show that the average time that task is sent until AGV finished picking up the task is 1.8632, the standard deviation is 0.9683, and the average time of the actual data is 1.7898, and the standard deviation is 0.7928. The above simulation results show that the model built in this paper has a good simulation of the actual multi-AVG storage system.
Keywords: System Modeling multi-AGV system simulation platform automated warehousing
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基于多AGV的自动化仓储系统仿真研究
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