基于变体马尔可夫博弈的自动引导车任务协同处理
Cooperative Processing of Tasks for Automatic Guided Vehicles Based on Variant Markov Game
赵鹏瑞 1任建伟 1王青 1冯晨曦1
作者信息
- 1. 内蒙古大学交通学院,呼和浩特 010070
- 折叠
摘要
为了提高转运仓库的转运效率,提出了一种基于变体马尔可夫博弈的自动引导车任务协同处理(VMG-AGV任务协同处理)方法.在利用FlexSim构建转运仓库模型的基础上对ProcessFlow、全局表、任务分配器、AGV等组件或实体进行参数、脚本设计,将VMG-AGV任务协同处理方法与传统的"一车带一物"拣选方法进行对比实验.仿真结果表明:新方法与传统方法相比,4辆AGV的平均利用率提高了11％,在制品平均运输量提高了 40％,4台出库合成器平均每小时增加出库4.5单.
Abstract
In order to improve the transfer efficiency of the transfer warehouse,a method of automatic guided vehicle task cooperative processing(VMG-AGV task cooperative processing)based on variant Markov game is proposed.Based on FlexSim,parameters and scripts of Process-Flow,global table,task distributor,AGV and other components or entities are designed,and the VMG-AGV task collaborative processing method is compared with the traditional"one cart with one object"picking method.The simulation results show that compared with the traditional meth-od,the average utilization rate of four AGVs is increased by 11％,the average delivery rate of four synthesizers is increased by 4.5 per hour,and the average transport volume of products in process is increased by 40％.
关键词
物流工程/任务协同处理/FlexSim/AGV系统/多智能体/仿真模拟Key words
logistics engineering/task collaborative processing/FlexSim/AGV system/multi-agent/simulation引用本文复制引用
基金项目
国家自然科学基金(71862026)
内蒙古高等学校青年科技英才支持计划(NJYT22095)
出版年
2024
NETL
NSTL
万方数据