基于排队论智能RGV的动态调度策略的研究
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摘要
文章通过分析无故障和CNC随机性故障RGV动态调度的各因素之间的时间关系,运用排队论和排列组合建立了两种RGV动态调度的计算模型,并给设计了相应的算法,分别对三种具体情况推导出的RGV动态调度模型,运用Excel和C#编程得出RGV的优化调度模型和系统的作业效率。对于单个直线轨道式RGV,得到最短时间及RGV在最短时间内回到初始CNC的最优组合,使得达到成料数量最多;对于CNC随机性故障问题,利用伯努利概率模型计算排除故障所需时间,得到有故障RGV动态调度的最优组合。
By analyzing the time difference among various factors of RGV dynamic scheduling with fault-free and CNC stochastic fault,this paper establishes two kinds of RGV dynamic scheduling calculation models based on Queuing theory and Permutation combination,and proposes corresponding algorithms design. The RGV dynamic scheduling model is deduced for three specific cases,and the optimal scheduling model and system operation of RGV are obtained by Excel and C# programming. Industry efficiency. As for single linear track RGV,the optimal combination of the shortest time and the return of the RGV to the initial CNC in the shortest time is obtained,so as to maximize the number of finished materials. As for the CNC stochastic fault problem,the Bernoulli probability model is used to calculate the time needed for troubleshooting,and the optimal combination of RGV dynamic scheduling with faults is obtained.
By analyzing the time difference among various factors of RGV dynamic scheduling with fault-free and CNC stochastic fault,this paper establishes two kinds of RGV dynamic scheduling calculation models based on Queuing theory and Permutation combination,and proposes corresponding algorithms design. The RGV dynamic scheduling model is deduced for three specific cases,and the optimal scheduling model and system operation of RGV are obtained by Excel and C# programming. Industry efficiency. As for single linear track RGV,the optimal combination of the shortest time and the return of the RGV to the initial CNC in the shortest time is obtained,so as to maximize the number of finished materials. As for the CNC stochastic fault problem,the Bernoulli probability model is used to calculate the time needed for troubleshooting,and the optimal combination of RGV dynamic scheduling with faults is obtained.
引文
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[4]杨少华,张家毅,赵立.基于排队论的环轨多车数量与能力分析[J].制造业自动化,2011,33(16):102-104.
[5]林铠,刘晓宇,宋传承.基于遗传算法的分序RGV动态调度策略[J].自动化应用,2018,(12):65-66+70.
[6]吴长庆,罗键,陈火国,等.基于Petri网的RGVs系统中环路死锁研究[J].计算机科学,2009,36(4):250-253.
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[8]张甜,宗泽华.基于遗传算法的RGV的动态调度模型研究[J].数字技术与应用,2018,(9):92-93.
[9]张桂琴,张仰森.直线往复式轨道自动导引车智能调度算法[J].计算机工程,2009,35(15):176-178.
[10]陈华,孙启元.基于TS算法的直线往复2-RGV系统调度研究[J].工业工程与管理,2015,(5):80-88.
[11]向旺,吴双,张可义.基于排队论的环形穿梭车系统运行参数分析[J].制造业自动化,2018,40(6):151-153.
[12]毛海勤.伯努利概型的教学探讨[J].数学学习与研究,2012,20(17):10-12.
[13]马震宇,王正鹤,徐梦飞.伯努利方程教学实验与数值仿真应用[J].实验室科学,2018,21(5):37-40+44.
[14]王海环,王俊.一种改进的多伯努利多目标跟踪算法[J].西安电子科技大学学报,2016,43(6):176-182.
[15]陈杰,鲍敏,吴海龙.基于排队论的理想在制品数学模型建立[J].机电工程,2017,(2):136-140.
[16]董皓,张伟,朱德桥,岳琦.论理论的自动化立体仓库系统运行参数分析[J].机械设计与制造,2010,(6):203-205.
[17]王文博,叶庆卫,周宇.基于排队论综合指标评估的动态负载均衡算法[J].电信科学,2018,34(7):86-91.
[18]徐瑞滢.基于排队论的城市道路通行能力分析方法[J].中国科技信息,2019,(2):93-95.
[2]Dotoli M,Fanti M P. Modeling of an AS/RS serviced by rail-guided vehicles with colored Petri nets:a control perspective. IEEE International Conference on Systems,Man and Cybernetics. IEEE,2003,62-167.
[3]Sáez D,Cortés C E,Núez A. Hybrid adaptive predictive control for the multi-vehicle dynamic pick-up and delivery problem based on genetic algorithms and fuzzy clustering. Computers&Operations Research, 2008, 35(11):3412-3438.
[4]杨少华,张家毅,赵立.基于排队论的环轨多车数量与能力分析[J].制造业自动化,2011,33(16):102-104.
[5]林铠,刘晓宇,宋传承.基于遗传算法的分序RGV动态调度策略[J].自动化应用,2018,(12):65-66+70.
[6]吴长庆,罗键,陈火国,等.基于Petri网的RGVs系统中环路死锁研究[J].计算机科学,2009,36(4):250-253.
[7]沃芸婷,禹一童.基于动态规划算法的RGV智能调度策略[J].工业技术创新,2018,5(6):44-47+52.
[8]张甜,宗泽华.基于遗传算法的RGV的动态调度模型研究[J].数字技术与应用,2018,(9):92-93.
[9]张桂琴,张仰森.直线往复式轨道自动导引车智能调度算法[J].计算机工程,2009,35(15):176-178.
[10]陈华,孙启元.基于TS算法的直线往复2-RGV系统调度研究[J].工业工程与管理,2015,(5):80-88.
[11]向旺,吴双,张可义.基于排队论的环形穿梭车系统运行参数分析[J].制造业自动化,2018,40(6):151-153.
[12]毛海勤.伯努利概型的教学探讨[J].数学学习与研究,2012,20(17):10-12.
[13]马震宇,王正鹤,徐梦飞.伯努利方程教学实验与数值仿真应用[J].实验室科学,2018,21(5):37-40+44.
[14]王海环,王俊.一种改进的多伯努利多目标跟踪算法[J].西安电子科技大学学报,2016,43(6):176-182.
[15]陈杰,鲍敏,吴海龙.基于排队论的理想在制品数学模型建立[J].机电工程,2017,(2):136-140.
[16]董皓,张伟,朱德桥,岳琦.论理论的自动化立体仓库系统运行参数分析[J].机械设计与制造,2010,(6):203-205.
[17]王文博,叶庆卫,周宇.基于排队论综合指标评估的动态负载均衡算法[J].电信科学,2018,34(7):86-91.
[18]徐瑞滢.基于排队论的城市道路通行能力分析方法[J].中国科技信息,2019,(2):93-95.