基于商品关联度的智能仓库储位分配问题研究

Research on Storage Allocation Problem of Intelligent Warehouse Based on Correlation Degree of Items

储位分配方案是直接影响智能仓库工作效率和拣选成本的关键因素.根据历史订单信息定义了商品之间的关联度,以同一货架上的商品之间的关联度之和极大化为目标建立了智能仓库储位分配问题的数学模型,并设计了求解模型的算法.首先根据历史订单信息计算商品之间的关联度,然后结合商品的周转率、商品之间的关联度等信息,设计了启发式算法求解智能仓库储位分配问题,并且分析了启发式算法的时间复杂度.通过大量的模拟计算验证了本文建立的数学模型和设计的启发式算法的有效性,证明了以同一货架上商品之间关联度极大化为目标和以订单拣选过程中搬运货架总次数极小化为目标的一致性.通过对比分析本文算法得到的储位分配结果与随机储位分配结果可以看出,利用基于商品关联度的启发式算法得到的储位分配方案比随机储位分配方案对应的货架搬运次数平均减少了30.08%.

The storage allocation strategy is the key factor that directly affects the working efficiency and picking costs of intelligent warehouse.Based on historical orders information,the correlation degree between items is defined.A mathematical model of intelligent warehouse storage allocation problem is formulated,the objective function of the model is to maximize the sum of the correlation degree between items on the same shelf.The algorithm for solving the model is proposed.Firstly,the correlation degrees between items are calculated based on historical orders information.Then,by considering the turnover rate of each item and the correlation degree between any pair of items,a heuristic algorithm is designed to solve the storage allocation problem of intelligent warehouse,and the time complexity of the heuristic algorithm is analyzed.A large number of simulations are done to verified the efficient of the proposed mathematical model and the heuristic algorithm.The consistency between maximizing the correlation degrees of items on the same shelf and minimizing the total number of shelves to be transported in order picking process is proved.By comparing and analyzing the storage allocation results obtained by the heuristic algorithm and the stochastic storage allocation scheme,it can be seen that the number of shelves to be transported in order picking process based on storage allocation results obtained by heuristic algorithm is 30.08%less than that of the stochastic storage allocation scheme.