Adaptive Storage Location Assignment for Warehouses Using Intelligent Products
Adaptive Storage Location Assignment for Warehouses Using Intelligent Products
复制标题
DOI：
10.1007/978-3-319-15159-5_25
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
N. Tsamis;V. Giannikas;D. McFarlane;Wenrong Lu;J. Strachan
中科院分区：
文献类型：
--
作者：
N. Tsamis;V. Giannikas;D. McFarlane;Wenrong Lu;J. Strachan
由于客户偏好的快速变化，订单拣选已成为订单履行流程效率的瓶颈，进而成为仓储公司客户满意度的负担。改进新交付产品的存储位置分配是提高拣选性能的一种有效方法。然而，大多数可用的存储策略提供静态解决方案，不能处理订单需求特征的频繁变化。本研究旨在通过针对存储位置分配问题开发分布式、自适应策略来确定潜在的解决方案，并遵循产品智能范式进行实施。通过使用本地电子商务履行仓库的数据进行模拟研究，探索了这种策略在实际工业系统中的效率。
Due to rapidly changing customer preferences, order-picking has become a bottleneck for the efficiency of the order fulfilment process and in turn a burden to the customer satisfaction of warehouse companies. Improved storage location assignment of newly delivered products is one effective method for improving the picking performance. However, most of the available storage policies provide static solutions that do not deal with frequent changes in order demand characteristics. This study aims to identify a potential solution by developing a distributed, adaptive strategy for the storage location assignment problem and follows the product intelligence paradigm for its implementation. The efficiency of such a strategy in real industrial systems is explored via a simulation study using data from a local e-commerce fulfilment warehouse.