概率资源约束下多品种库存系统的优化

为了有效利用库存资源,同时降低大型仓储配送中心的运行成本,需要对随机需求下的多品种库存问题进行深入研究。在原有单周期线性资源约束下的多品种订货策略的基础上,通过将一种概率形式的库存资源约束应用于多品种(Q,R)策略,实现对仓库面积和运营资金更为科学的管理和控制。同时还提出了一种有效的多项式启发式算法,为物流企业在实际库存管理中应用这一模型提供了解决方案。相对于已有的方法,在不增加资源使用量的情况下,该方法可以节约平均库存成本30%以上。

Optimization of a multi-item inventory system with probabilistic resource constraints

Multi-item inventory systems in stochastic demands were studied to reduce operation costs of large scale distribution centers and effectively use resources. This paper suggests an application of a probabilistic constraint in the context of multi-item (Q,R) ordering policy based on previous research on single period multi-item inventory systems with linear constraints, which significantly improves warehouse and capital management. An effective heuristic algorithm was developed, which provides enterprises with applicable solution in practical inventory management. The results of the polynomial algorithm show that over 30% of inventory costs is saved compared with conventional methods without further resource consumption.