Abstract: More and more intensive mobile shelves are used in storage practice, which improves the utilization of storage space, but increases the time cost of order picking at the same time. According to the storage layout characteristics of intensive mobile shelves, for the case where multiple channels can be opened at the same time, the rack moving time is converted into the channel moving distance for calculation, and an optimization rule for multiple channels to move in sequence is proposed. A mathematical model for order optimization of order picking is established with the objective of minimizing the total time spent in order picking of multiple orders in a batch. According to the characteristics of the model, a real-coded genetic algorithm with global optimization is designed, and simulations of different scales are performed. The calculation results show that the algorithm has strong applicability, which has significant optimization effects for different scale problems; small increases and decreases in the number of shelves, the number of orders, and the number of moving channels will cause large fluctuations in total picking time; when the initial positions of multiple moving channels are in the middle or are evenly dispersed, the total picking time is slightly better than that when they are concentrated at one end of the storage system.

Key words: intensive storage, moving shelves, order sequencing, picking time, genetic algorithm

摘要： 密集式移动货架越来越多地应用到仓储实践中,提高了仓储空间利用率,但增加了订单拣选的时间成本。本文根据密集式移动货架的仓储布局特点,针对多条通道可同时打开的情况,将货架移动时间转换成通道移动距离进行计算,提出了多条通道依次移动的优化规则,以整批订单拣选所耗费的总时间最少为目标,建立了订单拣选顺序优化的数学模型。针对该模型的特点,设计了实数编码且全局寻优的遗传算法,并进行了不同规模的算例模拟。计算结果表明,该算法具有较强的适用性,针对不同规模的问题,均有显著的优化效果;货架数量、订单数量以及移动通道数量的小幅度增减,将会导致总拣选时间较大幅度的波动;多条移动通道初始位置居于中部或均匀分散,总拣选时间略优于其集中于仓储系统一端。

关键词: 密集型仓储, 移动货架, 订单排序, 拣选时间, 遗传算法