多人拣选系统拥堵的马尔科夫建模与仿真研究

目的 为了降低拣选系统拥堵率提高应急物资的运输效率,文中提出一种基于马尔科夫的多人拥堵模型。方法 分别构建窄通道货位单件拣选和货位多件拣选情况下的马尔科夫状态转移矩阵,求解平稳分布,获得拣选概率与拥堵率的函数关系式,并通过仿真分析不同因素变化对拥堵率的影响。结果 研究发现在货位单件拣选情况下,拣选概率取值为0.3左右时,系统拥堵率达到峰值,之后随拣选概率的增大而减小;在货位多件拣选情况下,拣选概率与系统拥堵率呈正相关,系统拥堵率随着拣选概率的增加而增加。结论 在实际拣选作业中,为了降低系统拥堵率,货位单件拣选应尽量避免拣选概率在0.3左右;货位多件拣选应尽量降低拣选概率。

Markov Modeling and Simulation of Congestion in Multi-person Picking System

The work aims to propose a multi-person congestion model based on Markov, in order to reduce the congestion rate of the picking system and improve the transportation efficiency of emergency materials. The Markov state transition matrices of single picking in cargo slot and multiple picking in cargo slot in narrow channel were constructed to solve the stationary distribution, and obtain the functional relationship between the picking probability and the congestion rate. The effect of different factors on the congestion rate was analyzed by simulation. Under single picking in cargo slot, the system congestion rate reached its peak at the picking probability of about 0.3, and then decreased with the increase of the picking probability. Under multiple picking in cargo slot, the picking probability was positively correlated with the system congestion rate, and the system congestion rate increased with the increasing picking probability. Therefore, in the actual picking operation, in order to reduce the system congestion rate, the picking probability of about 0.3 should be avoided under single picking in cargo slot and under multiple picking, the picking probability should be reduced as much as possible.