Order Batching of Intelligent Warehouse Order Picking System Based on Logistics Robots
through the analysis of operation process of intelligent warehouse order picking system based on logistics robots, it is found that reducing the times of shelf moves and balancing the picking time among different picking stations arc key factors to improve the efficiency of order picking.Based on the correlation of different orders demand on the same shelf, the order batch model of parallel picking mode is established, with minimum picking time as optimization objective.The model uses the order correlation factor to describe the occupation of the same shelf by any two items of two orders, and minimizes the longest picking time to achieve time balance among different stations operated in parallel.An improved dynamic clustering algorithm is used to solve the model, wherein the orders are first clustered according to their correlation factor, and this is followed by dynamic balancing of the picking time among the stations.Simulation results show that, compared with order batching method which only considers reducing the times of shelf handling, the proposed method is more effective for improving the picking efficiency of one wave.
order batching logistics robots intelligent warehouse system improved dynamic clustering algorithm
Ruiping Yuan Juntao Li Kai Liu Huiling Wang
School of Information Beijing Wuzi University Beijing,China
国际会议
郑州
英文
28-34
2018-09-21（万方平台首次上网日期，不代表论文的发表时间）