基于物料周转率与需求相关性的储位分配优化策略与算法

优化储位分配策略是加快订单拣选速度和提高仓储效率的重要前提。在实际出入库操作中,物料可能具有一定的需求相关性,如螺钉与螺母。若这些需求相关度较高的物料被安排于距离较远的货位,将大大影响其拣选出库的效率。因此,本研究考虑不同储位分配方案的影响,提出将基于物料周转率的存储策略(COI)与物料需求相关度相结合的存储策略,使得周转频率高和相关度大的物料在仓库中的位置接近,且存储于更近仓库出入口的巷道货位。由于模型的计算规模随着参数增长呈指数式增长,本研究开发出一种近似算法,并通过实验证明,相较于商业软件,本算法可更为有效得获取问题的最优或近似解。最后通过实例分析,给出不同COI系数与物料需求度偏好下该仓库的可行储位分配方案

A Method for Storage Location Assignment considering COIand Demand Correlations

Optimizing storage assignment is essential for speeding-up order picking in warehouses, but the order picking activities concern factors such as demand correlations. For instance, screws and caps should be stacked close to each other in order to improve the picking productivity. We consider COI-based storage policy as well as the demand correlations, and therefore products in small batches but with frequent orders would be stored close to the exit of the warehouse. In addition, products with close relations would be stored in adjacent locations. The storage location assignment problem is formulated as a mixed integer linear programming model, but experimental results indicate that the problem is extremely computationally difficult. Therefore, we advocate a clustering method and develop a heuristic to give good solutions to this problem. Further experiments and case study reveal that our heuristic outperforms existing off-the-shelf commercial software in terms of both efficiency and effectiveness.