检修备品库的货位优化模型

Slotting optimization model for overhaul warehouses

为了对货位进行合理分配，以提高检修备品库的领料效率，分析了检修用料的特点，并综合生产环境和分销环境下仓库货位优化的思想，提出检修物料的确定相关性和统计相关性这两个概念。根据物料相关性及用料频率，建立了检修备品库货位分配的多目标优化数学模型。模型的优化目标是，既要尽量将关系密切的物料聚集摆放，又要尽量将使用频率高的物料靠近出入库口存储。最后采用蚁群算法求解了该NPC（non—deterministic polynomial complete）问题，与采用随机分配策略的仿真结果相比，领料效率提高了23％～28％。

The patterns of spares consumption in overhaul systems were analyzed to rationally assign storage locations to spares and improve the efficiency of overhaul warehouses. Deterministic and statistical relationships between the various spare parts were developed based on slotting optimization approaches for production and retail environments. Both the relationships between the various parts and their consumption frequencies were analyzed to establish a multi-objective optimization model for the storage location assignment in overhaul warehouses. In this model, closely related items are stored near each other, with items with high consumption frequencies stored close to the I/O point. The ant colony optimization method was utilized to solve the NPC problem. Comparison to simulations using a random storage assignment strategy shows that the picking efficiency is improved by 23% - 28%.